Medical systems and methods

Abstract

The method (500) may include causing a scanning device to perform one or more scans on an object (510). The method may also include obtaining scan data of the object based on the one or more scans (520). The method may also include generating one or more images of the object based on the scan data (530). The method may also include generating a diagnosis result based on the one or more images (540). The diagnosis result may at least indicate whether one or more suspected lesions are present in the object.

Description

Technical Field

[0001] The present specification relates generally to medical technology and, more particularly, to systems and methods for automated diagnosis. Background Art

[0002] Automatic diagnosis (e.g., computer-aided diagnosis (CAD)) can detect "abnormalities" in histological sections of tissues or organs through image analysis, reduce diagnosis time, and enable doctors to make more detailed diagnoses. Therefore, it is desirable to provide an automatic diagnosis system and / or method to improve the efficiency of automatic diagnosis. Summary of the invention

[0003] According to one aspect of the present specification, a system may include one or more storage devices and one or more processors configured to communicate with the one or more storage devices. The one or more storage devices may include a set of instructions. When the one or more processors execute the set of instructions, the one or more processors may be instructed to perform one or more of the following operations. The one or more processors may cause a scanning device to scan an object one or more times. The one or more processors may obtain scanning data of the object based on the one or more scans. The one or more processors may generate one or more images of the object based on the scanning data. The one or more processors may generate a diagnosis result based on the one or more images. The diagnosis result may at least indicate whether there are one or more suspected lesions in the object.

[0004] In some embodiments, diagnostic results may be generated based on a machine learning model.

[0005] In some embodiments, the diagnostic result may indicate lesion information, including at least one of the type of one or more suspected lesions, the size of one or more suspected lesions, the location of one or more suspected lesions, the characteristics of one or more suspected lesions, the severity of one or more suspected lesions, or subsequent treatment recommendations related to one or more suspected lesions.

[0006] In some embodiments, the lesion information may include the severity of one or more suspected lesions. The one or more processors may determine whether the severity of one or more suspected lesions is greater than a threshold. In response to determining that the severity of one or more suspected lesions is greater than the threshold, the one or more processors may generate a message indicating that the object requires priority treatment.

[0007] In some embodiments, the one or more processors may transmit the notification to the remote surgical device via a network.

[0008] In some embodiments, the lesion information may include the severity of one or more suspected lesions. A label associated with the severity may be assigned to the diagnosis result.

[0009] In some embodiments, the one or more processors may transmit the one or more images and / or diagnostic results to a target remote device via a network.

[0010] In some embodiments, the target remote device may include a picture archiving and communication system (PACS) or a post-processing workstation.

[0011] In some embodiments, the one or more processors may cause one or more images and diagnostic results to be displayed.

[0012] In some embodiments, the one or more processors may transmit instructions to the remote assistance device to direct the remote assistance device to arrange subsequent treatment related to the subject based on the diagnosis result.

[0013] In some embodiments, the remote assistance device may include at least one of a hospital information system (HIS), a laboratory information system (LIS), a radiology information system (RIS), a doctor's workstation, or a nurse's workstation.

[0014] In some embodiments, the one or more processors may be configured to allow one or more user devices to access the one or more processors via a network to view the one or more images and diagnostic results.

[0015] In some embodiments, based on one or more images and / or diagnostic results, modification of at least one of scanning parameters of one or more scans, reconstruction parameters for generating one or more images, or diagnostic results can be performed online by a first user device among one or more user devices.

[0016] In some embodiments, the modification may be viewed in real time via a second user device among the one or more user devices.

[0017] In some embodiments, one of the one or more user devices may be associated with a physician or an imaging technician.

[0018] According to another aspect of the content of this specification, a method may include one or more of the following operations. One or more processors may cause a scanning device to scan an object one or more times. The one or more processors may obtain scan data of the object based on the one or more scans. The one or more processors may generate one or more images of the object based on the scan data. The one or more processors may generate a diagnosis result based on the one or more images. The diagnosis result may at least indicate whether there are one or more suspected lesions in the object.

[0019] According to another aspect of the specification, a system may include a control module configured to cause a scanning device to scan an object one or more times. The system may also include a reconstruction module configured to obtain scan data of the object based on one or more scans. The reconstruction module may also be configured to generate one or more images of the object based on the scan data. The system may also include a diagnosis module configured to generate a diagnosis result based on the one or more images. The diagnosis result may at least indicate whether there are one or more suspected lesions in the object.

[0020] According to another aspect of the contents of this specification, a non-transitory computer-readable medium may include at least one set of instructions. The at least one set of instructions may be executed by one or more processors of a computing device. The one or more processors may cause a scanning device to scan an object one or more times. The one or more processors may obtain scan data of the object based on the one or more scans. The one or more processors may generate one or more images of the object based on the scan data. The one or more processors may generate a diagnosis result based on the one or more images. The diagnosis result may at least indicate whether there are one or more suspected lesions in the object.

[0021] Some additional features of this specification may be explained in the following description. Some additional features of this specification will be apparent to those skilled in the art through study of the following description and corresponding drawings or understanding of the production or operation of the embodiments. The features of this specification may be realized and obtained by practicing or using various aspects of the methods, means and combinations set forth in the detailed examples discussed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] This specification will be further described by exemplary embodiments. These exemplary embodiments will be described in detail by the accompanying drawings. These embodiments are non-limiting exemplary embodiments, in which the same numbers in each figure represent similar structures, wherein:

[0023] Figure 1 is a schematic diagram of an exemplary imaging system according to some embodiments of the present specification.

[0024] Figure 2 is a schematic diagram of hardware and / or software components of an exemplary computing device according to some embodiments of the present description.

[0025] Figure 3 is a schematic diagram of hardware and / or software components of an exemplary mobile device according to some embodiments of the present specification.

[0026] Figure 4 is a block diagram of an exemplary processing device according to some embodiments of this specification; and

[0027] Figure 5 It is a schematic diagram of an exemplary process for automatic diagnosis shown in some embodiments of the present specification. DETAILED DESCRIPTION

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. However, it should be understood by those skilled in the art that the present application can be implemented without these details. In other cases, in order to avoid unnecessarily obscuring the various aspects of the present application, well-known methods, processes, systems, components and / or circuits have been described at a higher level. For those of ordinary skill in the art, it is obvious that various changes can be made to the disclosed embodiments, and without departing from the principles and scope of the present application, the general principles defined in the present application can be applied to other embodiments and application scenarios. Therefore, the present application is not limited to the embodiments shown, but conforms to the broadest scope consistent with the scope of the application.

[0029] The terms used in this application are only for the purpose of describing specific example embodiments and are not restrictive. The singular forms "one", "an" and "the" used in this application may also include plural forms unless the context clearly indicates an exception. It should also be understood that when used in this specification, the terms "comprising" and "including" indicate the presence of the described features, integers, steps, operations, elements and / or group components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0030] It should be understood that the terms "system", "engine", "unit", "module" and / or "block" used herein are a method of distinguishing different components, elements, parts, portions, or assemblies at different levels in ascending order. However, if these terms achieve the same purpose, other expressions may be used instead.

[0031] Generally, the words "module", "unit" or "block" used herein refer to logic embodied in hardware or firmware, or a collection of software instructions. The modules, units or blocks described herein may be implemented as software and / or hardware and may be stored in any type of non-transitory computer-readable medium or other storage device. In some embodiments, software modules / units / blocks may be compiled and linked to an executable program. It should be understood that software modules may be called from other modules / units / blocks or from themselves, and / or may be called in response to detected events or interrupts. Software modules / units / blocks configured for execution on a computing device may be provided on a computer-readable medium, or as a digital download (and may be stored in a compressed or installable format, requiring installation, decompression or decryption before execution). The software code here may be partially or completely stored in a storage device of a computing device performing the operation, and applied in the operation of the computing device. Software instructions may be embedded in firmware, such as an EPROM. It should also be understood that hardware modules / units / blocks may be included in connected logic components, such as gates and triggers, and / or may include programmable units, such as programmable gate arrays or processors. The modules / units / blocks or computing device functions described herein may be implemented as software modules / units / blocks, but may be represented by hardware or firmware. Typically, the modules / units / blocks described herein refer to logical modules / units / blocks, which may be combined with other modules / units / blocks or divided into sub-modules / sub-units / sub-blocks, although they are physical organizations or storage devices. The description may apply to a system, an engine, or a portion thereof.

[0032] It is understood that, unless the context clearly indicates otherwise, when a unit, engine, module or block is referred to as being "on", "connected" or "coupled to" another unit, engine, module or block, it may be directly on, connected or coupled to or communicating with the other unit, engine, module or block, or there may be intermediate units, engines, modules or blocks. In the present application, the term "and / or" may include any one or more of the related listed items or combinations thereof. For example, "A and / or B" means including A, including B, or including A and B. The term "image" in the content of this specification is used to collectively refer to various forms of image data and / or images, including two-dimensional (2D) images, three-dimensional (3D) images, four-dimensional (4D) images, and the like. The terms "first", "second", "third", etc. are used to distinguish similar objects and do not indicate the specific ranking of the objects. The character " / " includes one of the related terms.

[0033] These and other features, characteristics and functions of the related structural elements and methods of operation, as well as assembly and manufacturing economy of the present specification may become more apparent from the following description of the accompanying drawings, which form a part of the present specification. However, it should be understood that the drawings are for illustration and description purposes only and are not intended to limit the scope of the present specification, and it should be understood that the drawings are not drawn to scale.

[0034] Provided herein are systems and methods for non-invasive biomedical imaging / treatment, for example, for disease diagnosis, disease treatment, or research purposes. In some embodiments, these systems may include imaging systems. Imaging systems may include single-modality systems and / or multi-modality systems. The term "mode" as used herein refers broadly to an imaging or therapeutic method or technique for collecting, generating, processing, and / or analyzing imaging information of a subject or treating a subject. Single-modality systems may include, for example, magnetic resonance imaging (MRI) systems, computed tomography (CT) systems, positron emission tomography (PET) systems, single photon emission computed tomography (SPECT) systems, X-ray systems, ultrasound systems, and the like. The multimodal system may include, for example, a positron emission tomography-magnetic resonance imaging (PET-MRI) system, a positron emission tomography-computed tomography (PET-CT) system, a single photon emission computed tomography-magnetic resonance imaging (SPECT-MRI) system, a single photon emission computed tomography-computed tomography (SPECT-CT) system, a magnetic resonance imaging-computed tomography (MRI-CT) system, etc. It should be noted that the medical system described below is for illustration purposes only and is not intended to limit the scope of this specification.

[0035] In some embodiments, these systems may include a treatment system. The treatment system may include a treatment plan system (TPS), an image-guided radiotherapy (IGRT) system, and the like. The image-guided radiotherapy (IGRT) system may include a treatment device and an imaging device. The treatment device may include a linear accelerator, a cyclotron, a synchrotron, and the like, configured to perform radiotherapy on a subject. The treatment device may include an accelerator of multiple particle types (e.g., including photons, electrons, protons, or heavy ions). The imaging device may include a single-mode device and / or a multi-mode device. A single-mode device may include, for example, a magnetic resonance (MR) scanning device, a CT scanning device, an X-ray scanning device, a PET scanning device, a SPECT scanning device, an ultrasound scanning device, and the like. A multi-mode device may include, for example, a PET-MRI scanning device, a PET-CT scanning device, a SPECT-MRI scanning device, a SPECT-CT scanning device, an MR-CT scanning device, and the like.

[0036] In this specification, a subject may include a biological object and / or a non-biological object. A biological object may be a human, an animal, a plant, or a specific part, organ and / or tissue thereof. For example, a subject may include a head, a neck, a chest, a heart, a stomach, a blood vessel, a soft tissue, a tumor, a nodule or the like, or any combination thereof. In certain embodiments, a subject may be an artificial component of an organic and / or inorganic substance with or without life. The terms "object" or "subject" are used interchangeably in this disclosure.

[0037] In the present specification, for the sake of brevity, a representation of an object (e.g., a patient, a subject, or a portion thereof) in an image may be referred to as an object. For example, for the sake of brevity, a representation of an organ or tissue (e.g., a heart, a liver, a lung) in an image may be referred to as an organ or tissue. In addition, for the sake of brevity, an image including a representation of an object may be referred to as an image of the object or an image including the object. Further, for the sake of brevity, an operation performed on a representation of an object in an image may be referred to as an operation performed on the object. For example, for the sake of brevity, segmentation of a portion of an image including a representation of an organ or tissue in the image may be referred to as segmentation of an organ or tissue.

[0038] One aspect of the present specification provides an automatic diagnosis system and method. In the present specification, in addition to being able to scan an object and generate one or more images of the object, the inspection terminal can also perform automatic diagnosis based on the generated one or more images. In this way, remote data transmission is omitted in the workflow from image generation to automatic diagnosis. The reconstructed image can be archived to the PACS together with the diagnosis results. The operator of the inspection terminal can view the diagnosis results directly on the console of the inspection terminal instead of accessing the PACS. Based on the diagnosis results, the operator of the inspection terminal can directly make a decision on the follow-up treatment of the patient so that the patient (especially emergency patients) can be given follow-up treatment as soon as possible.

[0039] Figure 1 is a schematic diagram of an exemplary imaging system according to some embodiments of the present specification.

[0040] Just as an example, Figure 1 As shown, imaging system 100 may include imaging device 110, processing device 120, storage device 130, one or more terminals 140, and network 150. The components in imaging system 100 may be connected in various ways. For example, Figure 1 As shown, the imaging device 110 may be connected to the processing device 120 via the network 150 or directly connected to the processing device 120 (as shown by the double-headed arrow in the dashed line connecting the imaging device 110 and the processing device 120). As another example, Figure 1 As shown, the terminal 140 may be connected to the processing device 120 via the network 150 or directly connected to the processing device 120 (as shown by the double-headed arrow in the dashed line connecting the imaging device 110 and the processing device 120).

[0041] The imaging device 110 may be configured to acquire imaging data (also referred to as scan data) associated with at least one portion of the object. The imaging device 110 may scan an object or a portion thereof located within its detection area and generate imaging data associated with the object or a portion thereof. In some embodiments, the imaging data associated with at least one portion of the object may include images (e.g., image slices), PET data (e.g., gamma photon information), SPECT data (e.g., gamma photon information), MR data (e.g., echo signals), CT data (e.g., projection data), or similar data, or a combination thereof. In some embodiments, the imaging data may be two-dimensional (2D) imaging data, three-dimensional (3D) imaging data, four-dimensional (4D) imaging data, or similar data, or any combination thereof. In some embodiments, the object may be biological or non-biological. For example, the object may include a patient, an artificial object, etc. As another example, the object may include a specific portion, organ, and / or tissue of a patient. For example, the object may include a head, neck, chest, heart, stomach, blood vessel, soft tissue, tumor, nodule, or the like, or any combination thereof. In some embodiments, the imaging device 110 may include a single-modality imaging device or a multi-modality device. Single-modality devices may include, for example, magnetic resonance (MR) scanning devices, CT scanning devices, X-ray scanning devices, PET scanning devices, SPECT scanning devices, ultrasonic scanning devices, etc. Multi-modality devices may include, for example, PET-MRI scanning devices, PET-CT scanning devices, SPECT-MRI scanning devices, SPECT-CT scanning devices, MR-CT scanning devices, etc.

[0042] The processing device 120 can process data and / or information obtained from the imaging device 110, the terminal 140, and / or the storage device 130. For example, the processing device 120 can cause the imaging device 110 to scan the object one or more times. The processing device 120 can obtain scan data of the object based on one or more scans. The processing device 120 can generate one or more images of the object based on the scan data. The processing device 120 can generate a diagnosis result based on the one or more images, and the diagnosis result at least indicates lesion information related to one or more suspected lesions of the object. The processing device 120 can transmit the one or more images and the diagnosis result to the target remote device through the network. In some embodiments, the processing device 120 can be a computer, a user console, a single server or a server group, etc. The server group can be centralized or distributed. In some embodiments, the processing device 120 can be local or remote. For example, the processing device 120 can access information and / or data stored in the imaging device 110, the terminal 140, and / or the storage device 130 through the network 150. As another example, the processing device 120 can be directly connected to the imaging device 110, the terminal 140, and / or the storage device 130 to access the stored information and / or data. In some embodiments, the processing device 120 can be implemented on a cloud platform. By way of example only, the cloud platform can include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-cloud cloud, a multi-cloud, or the like, or any combination thereof.

[0043] The storage device 130 may store data, instructions, and / or any other information. In some embodiments, the storage device 130 may store data obtained from the terminal 140 and / or the processing device 120. For example, the storage device 130 may store imaging data obtained by the imaging device 110. As another example, the storage device 130 may store one or more images. As a further example, the storage device 130 may store diagnostic results of one or more images. In some embodiments, the storage device 130 may store data and / or instructions, and the processing device 120 may execute or be used to execute the exemplary method / system described in this specification. For example, the storage device 130 may store data and / or instructions, and the processing device 120 may execute or be used to generate one or more images. As another example, the storage device 130 may store data and / or instructions, and the processing device 120 may execute or be used to generate diagnostic results. In some embodiments, the storage device 130 may include a mass storage device, a removable storage device, a volatile read-write memory, a read-only memory (ROM), or the like, or any combination thereof. Exemplary mass storage devices may include magnetic disks, optical disks, solid-state drives, and the like. Exemplary removable storage devices may include flash drives, floppy disks, optical disks, memory cards, compressed disks, tapes, and the like. Exemplary volatile read-write memory may include random access memory (RAM). Exemplary RAM may include dynamic RAM (DRAM), double data rate synchronous dynamic RAM (DDRSDRAM), static RAM (SRAM), thyristor RAM (T-RAM), and zero capacitance RAM (Z-RAM), and the like. Exemplary ROM may include mask ROM (MROM), programmable ROM (PROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), compact disk ROM (CD-ROM), and digital versatile disk ROM, and the like. In some embodiments, the storage device 130 may be implemented on a cloud platform. By way of example only, a cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-cloud cloud, a multi-cloud, and the like, or any combination thereof.

[0044] In some embodiments, the storage device 130 may be connected to the network 150 to communicate with one or more other components in the imaging system 100 (e.g., the processing device 120, the terminal 14, etc.). One or more components in the imaging system 100 may access data or instructions stored in the storage device 130 through the network 150. In some embodiments, the storage device 130 may be directly connected to or communicate with one or more other components in the imaging system 100 (e.g., the processing device 120, the terminal 140, etc.). In some embodiments, the storage device 130 may be part of the processing device 120.

[0045] In some embodiments, a user (e.g., a doctor, technician, operator, or engineer) may interact with the imaging system 100 through the terminal 140. For example, the user may set one or more scanning parameters (e.g., scanning protocols) through the interface of the terminal 140. As another example, the diagnosis result or one or more images may be displayed on the interface of the terminal 140. The user may perform one or more user operations (e.g., zoom in, zoom out, rotate, mark, store, upload, crop, etc.) on the diagnosis result or one or more images through the terminal 140. In some embodiments, the terminal 140 may include a mobile device 140-1, a tablet computer 140-2, a laptop computer 140-3, or a similar device, or any combination thereof. In some embodiments, the mobile device 140-1 may include a smart home device, a wearable device, a mobile device, a virtual reality device, an augmented reality device, or a similar device, or any combination thereof. In some embodiments, the smart home device may include a smart lighting device, a control device for a smart appliance, a smart monitoring device, a smart TV, a smart camera, an intercom, or a similar device, or any combination thereof. In some embodiments, the wearable device may include a bracelet, a foot cover, glasses, a helmet, a watch, clothing, a backpack, a smart accessory, or the like, or any combination thereof. In some embodiments, the mobile device may include a mobile phone, a personal digital assistant (PDA), a gaming device, a navigation device, a point of sale (POS) device, a laptop, a tablet, a desktop, or the like, or any combination thereof. In some embodiments, the virtual reality device and / or augmented reality device may include a virtual reality helmet, virtual reality glasses, a virtual reality patch, an augmented reality helmet, augmented reality glasses, an augmented reality patch, or the like, or any combination thereof. For example, the virtual reality device and / or augmented reality device may include Google Glass TM 、Oculus Rift TM 、Hololens TM 、GearVR TM In some embodiments, the terminal 140 may be a part of the processing device 120. In some embodiments, the terminal 140 may include a console of the imaging system 100 and / or one or more user devices (e.g., a mobile device, a tablet computer, a laptop computer, etc.), which respectively establish a connection (e.g., wireless communication) and communicate with the processing device 120 through applications installed in the one or more user devices.

[0046] The network 150 may include any suitable network that can facilitate the exchange of information and / or data of the imaging system 100. In some embodiments, one or more components of the imaging device 110, the terminal 140, the processing device 120, the storage device 130, etc. can communicate information and / or data with one or more other components of the imaging system 100 via the network 150. For example, the processing device 120 can obtain imaging data from the imaging device 110 via the network 150. For another example, the processing device 120 can obtain a user instruction from the terminal 140 via the network 150. The network 150 may be and / or include a public network (e.g., the Internet), a private network (e.g., a local area network (LAN), a wide area network (WAN), etc.), a wired network (e.g., an Ethernet network), a wireless network (e.g., a cellular network (such as a Long Term Evolution (LTE) network), a frame relay network, a virtual private network (“VPN”), a satellite network, a telephone network, a router, a hub, a switch, a server computer, and / or any combination thereof. By way of example only, the network 150 may include a cable network, a wired network, a fiber optic network, a telecommunications network, an intranet, a wireless local area network (WLAN), a metropolitan area network (MAN), a public switched telephone network (PSTN), a Bluetooth TM Network, ZigBee TM In some embodiments, the network 150 may include one or more network access points, such as a wireless network, a near field communication (NFC) network, or the like, or any combination thereof. In some embodiments, the network 150 may include one or more network access points. For example, the network 150 may include a wired and / or wireless network access point, such as a base station and / or an Internet exchange point, through which one or more components of the imaging system 100 may connect to the network 150 to exchange data and / or information.

[0047] In some embodiments, the imaging system 100 may communicate with one or more remote devices 160 via the network 150. For example, the remote device 160 may include one or more servers 161. The imaging system 100 (e.g., the storage device 130, the processing device 120, and / or the terminal 140) may establish communication (e.g., wireless communication) with one or more servers 161 of the remote device 160 via an application installed in the terminal 140 and / or the processing device 120. For example, the processing device 120 may transmit one or more images and / or a diagnosis result corresponding to the one or more images to the remote device 160. As another example, the processing device 120 may transmit a notification indicating that the object needs to be processed first to the remote device 160. As another example, the processing device 120 may transmit an instruction to the remote device 160 to instruct the remote device 160 to arrange a follow-up treatment related to the object according to the diagnosis result. In some embodiments, the remote device 160 may include a picture archiving and communication system (PACS), a post-processing workstation, a remote surgery device, a remote assistance device, etc., or any combination thereof. The assisting equipment may include a Hospital Information System (HIS), a Laboratory Information System (LIS), a Radiology Information System (RIS), a doctor's workstation, a nurse's workstation, or similar equipment, or any combination thereof.

[0048] It should be noted that the above description of the imaging system 100 is for illustrative purposes only and is not intended to limit the scope of the present specification. For those skilled in the art, various changes and modifications may be made under the guidance of the present specification. For example, the imaging system 100 may include one or more additional components and / or omit one or more components of the imaging system 100 described above. Additionally or alternatively, two or more components of the imaging system 100 may be integrated into one component. One component of the imaging system 100 may be implemented on two or more subcomponents.

[0049] Figure 2 2 is a schematic diagram of hardware and / or software components of an exemplary computing device according to some embodiments of the present specification. The computing device 200 may be used to implement any component of the imaging system 100 described herein. For example, the processing device 120 may be implemented on the computing device 200 through its hardware, software program, firmware, or a combination thereof. Although only one such computing device is shown, for convenience, the computer functions related to the imaging system 100 described herein may be implemented in a distributed manner on a number of similar platforms to distribute the processing load. Figure 2As shown, computing device 200 may include processor 210 , memory 220 , input / output (I / O) 230 , and communication port 240 .

[0050] Processor 210 can execute computer instructions (program code) and perform the functions of processing device 120 according to the techniques described herein. Computer instructions may include, for example, routines, programs, objects, components, signals, data structures, modules, and functions, which perform specific functions described herein. In some embodiments, processor 210 can execute instructions obtained from terminal 140. In some embodiments, processor 210 may include one or more hardware processors, such as a microcontroller, a microprocessor, a reduced instruction set computer (RISC), an application-specific integrated circuit (ASIC), an application-specific instruction set processor (ASIP), a central processing unit (CPU). Graphics processing unit (GPU), physical processing unit (PPU), microcontroller unit, digital signal processor (DSP), field programmable gate array (FPGA), advanced RISC machine (ARM), programmable logic device (PLD), any circuit or processor capable of performing one or more functions, or the like, or any combination thereof.

[0051] For illustrative purposes only, only one processor is described in the computing device 200. However, it should be noted that the computing device 200 in the present specification may also include multiple processors. Therefore, the operations and / or method steps described in the present specification that are performed by one processor may also be performed jointly or individually by multiple processors. For example, if the processor of the computing device 200 in the present specification simultaneously performs operation A and operation B, it should be understood that operation A and operation B may also be performed jointly or separately by two or more different processors in the computing device 200 (e.g., the first processor performs operation A, the second processor performs operation B, or the first and second processors jointly perform operations A and B).

[0052] The memory 220 may store data / information obtained from the imaging device 110, the terminal 140, the storage device 130, or any other component of the imaging system 100. In some embodiments, the memory 220 may include a mass storage device, a removable storage device, a volatile read-write memory, a read-only memory (ROM), etc., or any combination thereof. In some embodiments, the memory 220 may store one or more programs and / or instructions to execute the exemplary methods described in the present specification.

[0053] I / O 230 may input or output signals, data, and / or information. In some embodiments, I / O 230 may enable user interaction with processing device 120. In some embodiments, I / O 230 may include input devices and output devices. Exemplary input devices may include a keyboard, a mouse, a touch screen, a microphone, etc., or a combination thereof. Exemplary output devices may include a display device, a speaker, a printer, a projector, or a similar device, or a combination thereof. Exemplary display devices may include a liquid crystal display (LCD), a display based on a light emitting diode (LED), a flat panel display, a curved screen, a television device, a cathode ray tube (CRT), etc., or a combination thereof.

[0054] The communication port 240 can be connected to a network (e.g., network 150) to facilitate data communication. The communication port 240 can establish a connection between the processing device 120 and one or more components of the imaging system 100 (e.g., imaging device 110, terminal 140, or storage device 130), and / or establish a connection between the processing device 120 and one or more external devices (e.g., databases, external storage and image / data processing workstations, etc.). The connection can be a wired connection, a wireless connection, or a combination of both, enabling data transmission and reception. The wired connection can include an electric wire, an optical cable, a telephone line, or the like, or any combination thereof. The wireless connection can include a Bluetooth network, a Wi-Fi network, a WiMax network, a WLAN, a ZigBee network, a mobile network (e.g., 3G, 4G, 5G, etc.), or a similar network, or any combination thereof. In some embodiments, the communication port 240 can be a standardized communication port, such as RS232, RS485, etc. In some embodiments, the communication port 240 can be a specially designed communication port. For example, the communication port 240 may be designed according to the digital imaging and communications in medicine (DICOM) protocol.

[0055] In some embodiments, components of computing device 200 (e.g., processor 210, memory 220, I / O 230, or communication port 240) may be connected and communicate with each other via a bus. The bus may include hardware, software, or the like, or any combination thereof, to couple components of computing device 200. The bus may include at least one of a data bus, an address bus, an expansion bus, and a local bus. By way of example only, the bus may include a graphics bus (e.g., an accelerated graphics port (AGP), an extended industry standard architecture (EISA) bus, a front side bus (FSB), a super transport (HT) interconnect, an industry standard architecture (ISA) bus, an Infiniband interconnect, a low pin count (LPC) bus, a storage bus, a micro channel architecture (MCA) bus, a peripheral component interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a serial advanced technology attachment (SATA) bus, a video electronics standard association local bus (VLB), or the like, or any combination thereof. In some embodiments, the bus may include one or more buses. The bus may include any type of bus or interconnect, without limitation.

[0056] Figure 3 300 is a schematic diagram of hardware and / or software components of an exemplary mobile device according to some embodiments of the present specification. In some embodiments, one or more components of the imaging system 100 (eg, the terminal 140 ) may be implemented on the mobile device 300 .

[0057] like Figure 3 As shown, the mobile device 300 may include a communication unit 310, a display unit 320, a graphics processing unit (GPU) 330, a central processing unit (CPU) 340, an input / output (I / O) 350, a memory 360, and a storage unit 370. In some embodiments, any other suitable components, including but not limited to a system bus or a controller (not shown), may also be included in the mobile device 300. In some embodiments, a mobile operating system 361 (e.g., iOS, Android, Windows Phone, etc.) and one or more applications 362 may be loaded from the storage unit 370 to the memory 360 for execution by the CPU 340. The application 362 may include a browser or any other suitable mobile application for receiving and rendering information related to image processing or other information from the processing device 120. User interaction with the information stream may be implemented through the I / O 350 and provided to the processing device 120 and / or other components of the imaging system 100 through the network 150.

[0058] In order to implement the various modules, units and their functions described in the present specification, a computer hardware platform can be used as the hardware platform for one or more elements described herein. The hardware elements, operating system and programming language of such a computer are conventional in nature, and it is assumed that those skilled in the art are fully familiar with these technologies to adapt these technologies to generate the images described herein. The computer with the user interface elements can be used to implement a personal computer (PC) or another type of workstation or terminal device, although the computer can also be used as a server if properly programmed. It is believed that those skilled in the art are familiar with the structure, programming and general operation of such computer equipment, and therefore, the drawings should be self-explanatory.

[0059] Figure 4 4 is a block diagram illustrating an exemplary computing device according to some embodiments of the present specification. In some embodiments, the processing device 120 and / or the terminal 140 may be implemented on the computing device 400 through hardware, software programs, firmware, or a combination thereof. Figure 4 As shown, the computing device 400 may include a control module 410 , a reconstruction module 420 , a diagnosis module 430 , and an input / output (I / O) module 440 .

[0060] The control module 410 can enable the scanning device (e.g., Figure 1 An imaging device 110 of the imaging system 100 performs one or more scans on an object (eg, one or more regions of interest (ROI) of a patient).

[0061] The reconstruction module 420 may obtain scan data of the object according to one or more scan results.

[0062] The reconstruction module 420 may generate one or more images of the object based on the scan data.

[0063] The diagnosis module 430 can generate a diagnosis result based on one or more images. In some embodiments, the diagnosis result can at least indicate whether there are one or more suspected lesions in the object. In some embodiments, the diagnosis result can further indicate lesion information of one or more suspected lesions of the object.

[0064] The lesion information may include basic information of the subject, a judgment indicating that one or more suspected lesions may exist in the subject, the type of one or more suspected lesions (e.g., tumor, lung nodule, hemorrhage, etc.), a type associated with one or more suspected lesions (e.g., cancer, infectious disease, novel coronavirus (2019-nCoV), cerebral hemorrhage, etc.), the size of one or more suspected lesions, the outline of one or more suspected lesions, the location of one or more suspected lesions, the characteristics of one or more suspected lesions, the severity of one or more suspected lesions, a label corresponding to the diagnosis result of the severity, follow-up treatment recommendations for one or more suspected lesions, etc., or any combination thereof. The basic information of the subject may include name, age, gender, occupation, medical history, identity number, contact information (such as telephone number, email address, etc.), portrait photo of the subject, etc., or any combination thereof. The characteristics of one or more suspected lesions may include the morphology of one or more suspected lesions, the symptoms of one or more suspected lesions, physiological information of one or more suspected lesions (e.g., tissue density, etc.), etc.

[0065] The recommendation for follow-up treatment may include rescanning at least a portion of the subject, performing one or more other scans using the imaging device 110, such as an enhanced scan, a perfusion scan, etc., performing other physical examinations, sending directly to the operating room, determining which doctor will receive the patient, information indicating that the subject needs priority treatment based on the severity of one or more suspected lesions, or similar information, or any combination thereof. In some embodiments, the information indicating that the subject needs priority treatment may correspond to a situation where the severity of one or more suspected lesions is greater than a threshold.

[0066] In some embodiments, the diagnostic module 430 can determine whether the severity of one or more suspected lesions is greater than a threshold. In response to determining that the severity of one or more suspected lesions is greater than the threshold, the diagnostic module 430 can generate information indicating that the subject needs priority treatment. Alternatively, the diagnostic module 430 can generate a follow-up treatment recommendation for one or more suspected lesions, and send a message directly to the remote assistance device based on the follow-up treatment recommendation to enable the nurse and doctor to prepare for follow-up treatment (e.g., surgery) as soon as possible.

[0067] In some embodiments, one or more generated images and / or diagnostic results may be displayed in terminal 140 (e.g., display unit 320). The diagnostic results may be displayed in the form of text, picture, voice, video, or the like, or any combination thereof. For example, one or more suspected lesions may be emphasized in one or more images. As another example, terminal 140 may present information indicating that the object requires priority treatment by voice broadcast, activating an alarm bell and / or an alarm light, or a similar method. In some embodiments, a user may perform one or more user operations (e.g., zoom in, zoom out, rotate, mark, store, upload, crop, etc.) on the diagnostic results or one or more images through terminal 140.

[0068] The I / O module 440 may transmit one or more images and diagnosis results to a target remote device (eg, the remote device 160 ) through a network (eg, the network 150 ).

[0069] In some embodiments, the diagnosis module 430 can generate a label corresponding to the severity of the object for the diagnosis result. For example, the diagnosis module 430 can identify the severity of the diagnosis result through text recognition, and generate a label corresponding to the identified severity of the object for the diagnosis result. After the diagnosis result is transmitted to the PACS server, the label assigned to the diagnosis result corresponding to the severity can enable the PACS server to sort the diagnosis results based on the severity, so that the diagnosis results viewed in the PACS can be arranged in descending order. In this way, the diagnosis results corresponding to the relatively high severity are given priority so that they can be viewed and / or processed by the doctor. For example, if the imaging device 110 is used continuously to examine multiple patients (for example, during the 2019-nCoV outbreak), for each patient, the diagnosis module 430 can generate a diagnosis result including the severity and a label corresponding to the severity. The diagnosis results can be transmitted to the PACS and arranged in descending order by severity in the PACS so that the doctor can determine which patient should be treated first based on the order of arrangement of the diagnosis results.

[0070] In some embodiments, the I / O module 440 may send instructions to the remote assistance device to direct the remote assistance device to arrange subsequent processing of the object based on the diagnosis result.

[0071] In some embodiments, if the diagnosis result includes information indicating that the subject needs priority treatment, the operator of the imaging system 100 can immediately contact the corresponding doctor and prompt the doctor to diagnose and treat the patient as soon as possible. Alternatively, the I / O module 440 can automatically send a notification indicating that the patient needs priority treatment to the doctor's workstation, prompting the corresponding doctor to diagnose and treat the patient as soon as possible.

[0072] In some embodiments, if the diagnosis result includes a suggestion that the patient needs to be operated on as soon as possible, the operator of the imaging system 100 can immediately contact the corresponding doctors and nurses and make an appointment for the operating room. Alternatively, the I / O module 440 can automatically transmit a notification indicating that the patient needs to be operated on as soon as possible to the doctor's workstation, the nurse's workstation, and the remote surgery device, prompting the corresponding doctors and nurses to prepare for the operation as soon as possible.

[0073] In some embodiments, if the diagnosis includes a recommendation to perform another examination, the operator of the imaging system 100 can schedule an appointment for the recommended examination. Alternatively, the I / O module 440 can automatically schedule the recommended examination by accessing, for example, a hospital information system (HIS), a laboratory information system (LIS), or a radiology information system (RIS).

[0074] It should be noted that the above description is only for illustration purposes, not for limiting the scope of this specification. Obviously, for those with ordinary skills in the art, various changes and modifications can be made according to the teachings of this specification. However, these changes and modifications do not deviate from the scope of this specification. Each of the above modules can be a hardware circuit, which is designed to perform certain actions, for example, according to a set of instructions stored in one or more storage media, and / or any combination of a hardware circuit and one or more storage media. In some embodiments, the computing device 400 may include one or more additional modules, such as a storage module (not shown) for storing data. In some embodiments, one or more modules of the computing device 400 may be omitted. In some embodiments, two or more modules of the computing device 400 may be integrated into one module.

[0075] Figure 5 is an exemplary flowchart for automatic diagnosis according to some embodiments of the present specification. In some embodiments, process 500 can be implemented as a set of instructions (e.g., application program) stored in a storage device (e.g., storage device 130, memory 220, etc.). Processing device 120 (e.g., processor 210 and / or Figure 4 The set of instructions may be executed by the processor 120 (or one or more modules described in the description), and when executing the instructions, the processor 120 may be configured to perform the process 500. The operations of the illustrated process described below are for illustration purposes. In some embodiments, the process 500 may be completed by one or more additional operations not described and / or without one or more of the operations discussed. In addition, Figure 5 The order in which the operations of process 500 are illustrated in FIG. 5 and the following description is not meant to be limiting.

[0076] At 510, the processing device 120 (eg, the control module 410) may cause the scanning device (eg, Figure 1An imaging device 110 of the imaging system 100 performs one or more scans on an object (eg, one or more regions of interest (ROI) of a patient).

[0077] In some embodiments, a user (e.g., a doctor, an operator, a technician, an engineer, etc.) can set one or more scanning parameters of a scan through the terminal 140. For example, for a CT scan, the user can set the position of components (e.g., a scanning table, a detector, an X-ray tube, a gantry) of the imaging device 110, the collimator aperture, the X-ray tube voltage and / or current, the moving speed of the scanning table, the rotation speed of the gantry, the field of view (FOV), the scanning time, etc. The terminal 140 can transmit the scanning parameters to the processing device 120. The processing device 120 can cause the imaging device 110 to scan the object one or more times according to the scanning parameters.

[0078] At 520 , the processing device 120 (eg, the reconstruction module 420 ) may obtain scan data of the object based on the one or more scans.

[0079] In some embodiments, the scan data (also referred to as imaging data) of the object may include images (e.g., image slices), PET data (e.g., gamma photon information), SPECT data (e.g., gamma photon information), MR data (e.g., echo signals), CT data (e.g., projection data), or the like, or any combination thereof. In some embodiments, the scan data may be two-dimensional (2D) scan data, three-dimensional (3D) scan data, four-dimensional (4D) scan data, etc., or any combination thereof.

[0080] In some embodiments, processing device 120 may obtain scan data from imaging device 110. Alternatively, the scan data may be obtained by imaging device 110 and stored in a storage device (e.g., storage device 130, storage device 220, storage unit 370, or an external source). Processing device 120 may retrieve the scan data from the storage device.

[0081] In 530, the processing device 120 (e.g., the reconstruction module 420) may generate one or more images of the object based on the scan data. In some embodiments, the user may input a reconstruction protocol through the terminal 140. The terminal 140 may transmit the reconstruction protocol to the processing device 120. The processing device 120 may generate one or more images of the object by reconstructing the scan data based on the reconstruction protocol. The reconstruction protocol may include a reconstruction algorithm, an image processing algorithm (e.g., an image segmentation algorithm, an image fusion algorithm, an image registration algorithm, an image rendering algorithm, a multi-plane reconstruction algorithm, a curved plane reconstruction algorithm), etc. In some embodiments, the one or more images may include a two-dimensional image, a three-dimensional image, a four-dimensional image (e.g., a series of two-dimensional or three-dimensional images arranged in time sequence), etc. In some embodiments, the one or more images may include a PET image, a SPECT image, an MR image, a CT image, etc., or any combination thereof.

[0082] In 540, the processing device 120 (e.g., the diagnostic module 430) may generate a diagnostic result based on the one or more images. In some embodiments, the diagnostic result may at least indicate whether one or more suspected lesions are present in the object. In some embodiments, the diagnostic result may further indicate lesion information of the one or more suspected lesions of the object.

[0083] In some embodiments, the processing device 120 can automatically generate a diagnosis result by analyzing one or more images using existing automatic diagnosis technology. For example, the processing device 120 can obtain one or more trained diagnostic models. The processing device 120 can input one or more images into the one or more trained diagnostic models. The one or more trained diagnostic models can segment one or more images into one or more regions of interest (ROIs) and generate a diagnosis result based on the one or more ROIs. As another example, a user can manually draw one or more ROIs of one or more images through the terminal 140. The processing device 120 can obtain one or more trained diagnostic models. The processing device 120 can input one or more images with one or more ROIs into the one or more trained diagnostic models. The one or more trained diagnostic models can generate a diagnosis result based on one or more ROIs.

[0084] As used herein, lesions refer to pathological changes in the morphology and function of human tissues and organs, such as some symptoms caused by bacterial and viral invasion (e.g., inflammatory infection, ulcers, tumors, etc.). Suspected lesions refer to at least a portion of one or more ROIs segmented from one or more images and regarded as lesions by automatic diagnosis (e.g., one or more trained diagnostic models). Lesion information may include basic information of the object, a determination indicating the possibility of the presence of one or more suspected lesions in the object, the type of one or more suspected lesions (e.g., tumors, lung nodules, hemorrhages, etc.), the type of disease associated with one or more suspected lesions (e.g., cancer, infectious diseases (such as 2019 novel coronavirus (2019-nCoV)), cerebral hemorrhage, etc.), the size of one or more suspected lesions, the outline of one or more suspected lesions, the location of one or more suspected lesions, the characteristics of one or more suspected lesions, the severity of one or more suspected lesions, the label assigned to the diagnostic result corresponding to the severity, the follow-up treatment recommendations for one or more suspected lesions, or the like, or any combination thereof. The basic information of the object may include name, age, gender, occupation, medical history, identity number, contact information (such as telephone number, email address, etc.), portrait photo of the object, etc., or any combination thereof. The features of the one or more suspected lesions may include the morphology of the one or more suspected lesions, the symptoms of the one or more suspected lesions, the physiological information of the one or more suspected lesions (such as tissue density, etc.), etc. In some embodiments, the type of the one or more suspected lesions, the type of disease associated with the one or more suspected lesions, and / or the severity of the one or more suspected lesions may be set by the terminal 140.

[0085] The recommendation for follow-up treatment may include rescanning at least a portion of the subject, performing one or more other scans (e.g., enhanced scans, perfusion scans, etc.) using imaging device 110, performing other physical examinations, sending directly to an operating room, determining which physician will receive the patient, information indicating that the subject requires priority treatment based on the severity of one or more suspected lesions, or similar information, or any combination thereof. In some embodiments, the information indicating that the subject requires priority treatment may correspond to a situation where the severity of one or more suspected lesions is greater than a threshold.

[0086] In some embodiments, the severity of one or more suspected lesions can be expressed in various forms. Just as an example, the severity can be expressed by a score, and a higher score can indicate that the suspected lesion is more serious. For example, a mild case of 2019-nCoV can be assigned a severity score that is smaller than the score of a severe case of 2019-nCoV. For another example, a disease that needs to be treated as soon as possible (such as cerebral hemorrhage) can be assigned a severity with a relatively high score (such as the highest score).

[0087] In some embodiments, the processing device 120 can determine whether the severity of one or more suspected lesions is greater than a threshold. In response to determining that the severity of one or more suspected lesions is greater than a threshold, the processing device 120 can generate information indicating that the object needs priority treatment. Alternatively, the processing device 120 can generate follow-up treatment recommendations for one or more suspected lesions, and send a message directly to the remote assistance device based on the follow-up treatment recommendations so that nurses and doctors can prepare for follow-up treatment (e.g., surgery) as soon as possible. In some embodiments, the threshold can be manually set by the user based on an empirical value. In some embodiments, the threshold can be set based on the default settings of the imaging system 100. In some embodiments, the threshold can be automatically determined by the processing device 120 using, for example, a machine learning model. For example, if the total score is 10, the threshold can be set to 5, 6, 7, 8, or 9.

[0088] As just an example, the processing device 120 may determine that there are one or more bleeding points in the brain of the subject by analyzing one or more images of the subject, and that the subject's disease is cerebral hemorrhage, and surgery is required as soon as possible. The processing device 120 may assign the highest severity score of 10 to the subject. The processing device 120 may determine that the severity of the subject is greater than a threshold of 7. In response to determining that the severity of the subject is greater than the threshold, the processing device 120 may generate a message indicating that the subject requires priority treatment, and send the message to the remote assistance device so that the nurse and the doctor can prepare for surgery as soon as possible.

[0089] In some embodiments, one or more generated images and / or diagnostic results may be displayed in terminal 140 (e.g., display unit 320). The diagnostic results may be displayed in the form of text, pictures, voice, video, or the like, or any combination thereof. For example, one or more suspected lesions may be emphasized in one or more images. As another example, terminal 140 may present information indicating that the object requires priority treatment by voice broadcast, activating an alarm bell and / or an alarm light, or the like. In some embodiments, a user may perform one or more user operations (e.g., zoom in, zoom out, rotate, mark, store, upload, crop, etc.) on the diagnostic results or one or more images through terminal 140.

[0090] In 550, the processing device 120 (e.g., the I / O module 440) may transmit one or more images and diagnostic results to a target remote device (e.g., the remote device 160) via a network (e.g., the network 150). In some embodiments, the remote device 160 may include a picture archiving and communication system (PACS), a post-processing workstation, a remote surgery device, a remote assistance device, or the like, or any combination thereof. The assistance device may include a hospital information system (HIS), a laboratory information system (LIS), a radiology information system (RIS), a doctor's workstation, a nurse's workstation, or the like, or any combination thereof.

[0091] In some embodiments, one or more images and / or diagnostic results may be archived in a PACS. For example, a PACS application may be installed on the terminal 140, and a user may upload one or more images and diagnostic results to a PACS server (e.g., server 161) through the network 150 from, for example, the storage device 130, the processing device 120, or the terminal 140 through the PACS application. Other users may access the PACS server through the PACS application installed on their personal terminals to browse and / or download one or more images and diagnostic results.

[0092] In some embodiments, the processing device 120 can generate a label corresponding to the severity of the object for the diagnosis result. For example, the processing device 120 can identify the severity of the diagnosis result through text recognition, and generate a label corresponding to the severity of the identified object for the diagnosis result. After the diagnosis result is transmitted to the PACS server, the label assigned to the diagnosis result corresponding to the severity can enable the PACS server to sort the diagnosis results according to the severity, so that the diagnosis results to be viewed in the PACS can be arranged in descending order. In this way, the diagnosis results corresponding to relatively high severity are given priority to be viewed and / or processed by the doctor. For example, if the imaging device 110 is used continuously to examine multiple patients (for example, during the 2019-nCoV outbreak), for each patient, the processing device 120 can generate a diagnosis result including a severity and a label corresponding to the severity. The diagnosis results can be transmitted to the PACS and arranged in descending order of severity in the PACS so that the doctor can determine which patient should be treated first based on the order in which the diagnosis results are arranged.

[0093] In some embodiments, the processing device 120 may transmit instructions to the remote assistance device to instruct the remote assistance device to arrange subsequent processing of the object according to the diagnosis result.

[0094] In some embodiments, if the diagnosis result includes information indicating that the subject needs priority treatment, the operator of the imaging system 100 can immediately contact the corresponding doctor and prompt the doctor to diagnose and treat the patient as soon as possible. Alternatively, the processing device 120 can automatically send a notification indicating that the patient needs priority treatment to the doctor's workstation, prompting the corresponding doctor to diagnose and treat the patient as soon as possible.

[0095] In some embodiments, if the diagnosis result includes a prompt that the patient needs to be operated on as soon as possible, the operator of the imaging system 100 can immediately contact the corresponding doctors and nurses and make an appointment for the operating room. Alternatively, the processing device 120 can automatically transmit a notification indicating that the patient needs to be operated on as soon as possible to the doctor's workstation, the nurse's workstation, and the remote surgery device, prompting the corresponding doctors and nurses to prepare for the operation as soon as possible.

[0096] In some embodiments, if the diagnosis includes a recommendation to perform another examination, the operator of the imaging system 100 can schedule the recommended examination. In addition, the processing device 120 can automatically schedule the recommended examination by accessing, for example, a hospital information system (HIS), a laboratory information system (LIS), or a radiology information system (RIS).

[0097] In some embodiments, one or more user devices (e.g., one or more terminals 140 (e.g., mobile device 140-1, tablet computer 140-2, laptop computer 140-3, etc.)) can establish a connection (e.g., wireless communication) and communicate with the processing device 120 through applications installed in the one or more user devices, respectively. Instead of accessing the PACS, the one or more user devices can directly access the processing device 120 to view one or more images and / or diagnostic results. If the PACS is accessed, the one or more images and / or diagnostic results need to be first transmitted from the imaging system 100 to the PACS. In this way, by omitting the transmission of data to the PACS, the doctor can know or make a diagnosis result for the patient (especially an emergency patient) as soon as possible.

[0098] In some embodiments, the user may modify at least one of the scan parameters of the one or more scans, the reconstruction parameters used to generate the one or more images, and the diagnosis results online through their user device. In some embodiments, the user may include a physician or an imaging technician.

[0099] In some embodiments, after the first imaging technician sets the scanning parameters for scanning the patient and the reconstruction parameters for generating one or more images of the patient through the console of the imaging system 100, the second imaging technician (e.g., the imaging device 110) away from the imaging system 100 can modify the scanning parameters and / or reconstruction parameters through its user device. The processing device 120 can scan the patient according to the modified scanning parameters and / or generate one or more images of the patient according to the modified reconstruction parameters.

[0100] In some embodiments, after performing a first scan on a patient and generating one or more images of the patient based on the first scan, an imaging technician remote from the imaging system 100 (e.g., the imaging device 110) can access the processing device 120 to view the one or more images and / or the diagnosis results. The imaging technician can modify the scan parameters of the first scan and / or the reconstruction parameters used to generate the one or more images through his user device based on the one or more images (e.g., the image quality of the one or more images) and / or the diagnosis results. The processing device 120 can perform a second scan on the patient based on the modified scan parameters, and / or reconstruct the image based on the scan data obtained in the first scan or the second scan and the modified reconstruction parameters. For example, if the imaging technician is not satisfied with the quality of one or more images, the imaging technician can modify the scan parameters and / or the reconstruction parameters used to generate the one or more images through his user device to improve the image quality.

[0101] In some embodiments, the doctor can modify the diagnosis result through his user device, such as modifying or deleting the follow-up treatment recommendation in the diagnosis result, adding a new follow-up treatment recommendation in the diagnosis result, or modifying the severity in the diagnosis result.

[0102] In some embodiments, when a first user performs a modification on at least one of the scanning parameters of one or more scans, the reconstruction parameters for generating one or more images, or the diagnostic results through his or her user device (also referred to as the first user device), a second user who accesses the processing device 120 through a second user device during the same time period as the first user is able to view real-time updates of the scanning parameters, reconstruction parameters, and / or diagnostic results (synchronized with the modification operation of the first user).

[0103] For example, after generating images and diagnostic results for a patient with cerebral hemorrhage, the processing device 120 may transmit a message indicating that the patient requires priority surgery to a remote surgery device and / or a remote assistance device. After receiving the message, the doctor in charge of the patient may directly access the processing device 120 through his user device (e.g., the doctor's smartphone, tablet computer, laptop computer, etc.) to view the patient's images and diagnostic results. If one of the doctors modifies the subsequent treatment recommendations in the diagnostic results online through his user device, the modification of the subsequent treatment recommendations may be provided in real time to the user devices of other doctors who view the diagnostic results by accessing the processing device 120, which may help other doctors understand the latest treatment methods and prepare for surgery in a timely manner. In some embodiments, doctors and / or imaging technicians with insufficient diagnostic experience may access the processing device 120 to view real-time modification operations on the diagnostic results, thereby learning diagnostic experience online.

[0104] For another example, an imaging technician who has little experience in operating the imaging system 100 can access the processing device 120 to view the real-time modification operations of the scanning parameters and / or reconstruction parameters, thereby learning online how to generate high-quality images.

[0105] In some embodiments, the imaging system 100 may be referred to as an inspection terminal. Generally speaking, the function of the inspection terminal is to scan an object (e.g., a patient) and generate one or more images of the object. For example, the imaging device 110 may be placed in a scanning room. The operator of the inspection terminal inputs a scanning protocol and / or a reconstruction protocol through a console (e.g., terminal 140) to control the scanning and image reconstruction of the object. Generally speaking, the console may be set in a control room separated from the scanning room by a glass window so that the operator can use the imaging device 110 to monitor the scanning of the object. The console may enable the processing device 120 to control the imaging device 110 to scan the object according to the scanning protocol, and enable the processing device 120 to generate one or more images of the object according to the scanning data generated by the scanning object.

[0106] The inspection terminal (eg, the processing device 120 or the terminal 140 ) may transmit one or more images to a remote device (eg, the remote device 160 ) via a network (eg, the network 150 ).

[0107] For example, the examination terminal may transmit one or more images to a picture archiving and communication system (PACS) through the network 150. The PACS may generate a diagnosis result by performing automatic diagnosis based on the one or more images, for example, using the server 161. A doctor may access the PACS to obtain the diagnosis result and perform subsequent treatment on the subject according to the diagnosis result.

[0108] As another example, the examination terminal can transmit one or more images to the PACS through the network 150. The doctor can access the PACS to obtain one or more images and use a personal terminal or a post-processing workstation to generate a diagnosis result. The doctor can perform subsequent treatment on the subject based on the diagnosis result.

[0109] As another example, the inspection terminal may transmit one or more images to a post-processing workstation via the network 150. The post-processing workstation may generate a diagnosis result by performing automatic diagnosis based on the one or more images, for example using the server 161. The post-processing workstation may archive the diagnosis result in a PACS. A doctor may access the PACS or the post-processing workstation to obtain the diagnosis result and perform subsequent treatment on the subject according to the diagnosis result.

[0110] As can be seen from the above, in the traditional clinical diagnosis workflow involving automatic diagnosis, since the inspection terminal cannot perform automatic diagnosis, the inspection terminal needs to transmit the generated one or more images to a remote device (such as a PACS or a post-processing workstation) through the network 150 to achieve automatic diagnosis. In this case, the time interval from image reconstruction to automatic diagnosis may be relatively long and depends on the data transmission speed between the inspection terminal and the remote device. For example, for dynamic imaging, the number of images generated is large (for example, tens of thousands of images), so data transmission may be slow. In addition, for emergency patients, this long time interval may be fatal. In cases where there are many patients (for example, during epidemic outbreaks such as 2019-nCoV), this long time interval reduces diagnostic efficiency. In addition, the interface and protocol of the remote device may be inconsistent with the inspection terminal, which increases the difficulty of data transmission between the remote device and the inspection terminal.

[0111] In the present specification, in addition to being able to scan an object and generate one or more images of the object, the inspection terminal (e.g., the imaging system 100) can perform automatic diagnosis based on the generated one or more images. For example, the automatic diagnosis can be performed by the processing device 120 or the terminal 140. In this way, in the workflow from image generation to automatic diagnosis, remote data transmission is omitted. The reconstructed image can be archived to the PACS together with the diagnosis results. The operator of the imaging system 100 can view the diagnosis results directly on the console of the inspection terminal (e.g., the terminal 140 of the imaging system 100) without accessing the PACS. Based on the diagnosis results, the operator of the inspection terminal can directly make a decision on the follow-up treatment of the patient, so that the patient (especially the emergency patient) can be treated as soon as possible.

[0112] It should be noted that the above description of process 500 is for illustrative purposes only and is not intended to limit the scope of this specification. A person having ordinary skills in the art may make various changes and modifications based on the teachings of this specification. However, such changes and modifications do not deviate from the scope of this specification. For example, the process 500 may be performed by the terminal 140 (e.g., the CPU 340, the GPU 330 and / or Figure 4 One or more modules shown in ) are executed.

[0113] The basic concepts have been described above. Obviously, for those of ordinary skill in the art who have read this application, the above invention disclosure is only for example and does not constitute a limitation of this application. Although not explicitly stated here, those of ordinary skill in the art may make various modifications, improvements and amendments to this application. Such modifications, improvements and amendments are suggested in this application, so such modifications, improvements and amendments still belong to the spirit and scope of the exemplary embodiments of this application.

[0114] At the same time, the present application uses specific words to describe the embodiments of the present application. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of the present application. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more in different positions in this specification does not necessarily refer to the same embodiment. In addition, some features, structures or characteristics in one or more embodiments of the present application can be appropriately combined.

[0115] In addition, it will be appreciated by those skilled in the art that various aspects of the present application may be illustrated and described by a number of patentable categories or situations, including any new and useful combination of processes, machines, products or substances, or any new and useful improvements thereto. Therefore, various aspects of the present application may be implemented entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or in combination with software and hardware implementations, which are generally referred to herein as "units," "modules," or "systems." In addition, various aspects of the present application may take the form of a computer program product embodied in one or more computer-readable media, the one or more computer-readable media having computer-readable program code embodied thereon.

[0116] A non-transitory computer readable signal medium may include a propagated data signal containing a computer readable program code, for example, in baseband or as part of a carrier wave. Such propagated signals may be in a variety of forms, including electromagnetic, optical, etc., or any suitable combination. A computer readable signal medium may be any computer readable medium other than a computer readable storage medium that may be connected to an instruction execution system, device, or apparatus to communicate, propagate, or transmit a program for use. The program code on a computer readable signal medium may be propagated via any suitable medium, including radio, cable, fiber optic cable, RF, etc., or any combination of the above.

[0117] The computer program code for performing the operation of various aspects of the application can be written in any combination of one or more programming languages, including object-oriented programming languages, such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB.NET, Python, VisualBasic, Fortran2003, Perl, COBOL2002, PHP, ABAP, dynamic programming languages ​​(such as Python, Ruby and Groovy) or other programming languages. The program code can be run completely on the user's computer, or run on the user's computer as an independent software package, or partly run on the user's computer and partly run on the remote computer, or run completely on the remote computer or server. In the latter case, the remote computer can be connected to the user's computer by any type of network (including local area network (LAN) or wide area network (WAN)), or can be connected to an external computer (for example, by using the network of a network service provider) or in a cloud computing environment or as a service, for example, software as a service (SaaS).

[0118] In addition, unless explicitly stated in the claims, the order of the processing elements and sequences described in this application, the use of alphanumeric characters, or the use of other names are not intended to limit the order of the processes and methods of this application. Although the above disclosure discusses some invention embodiments that are currently considered useful through various examples, it should be understood that such details are only for illustrative purposes, and the attached claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that are consistent with the essence and scope of the embodiments of this application. For example, although the implementation of the various components described above can be embodied in a hardware device, it can also be implemented as a pure software solution, for example, installation on an existing server or mobile device.

[0119] Similarly, it should be noted that in order to simplify the description disclosed in this application and thus help understand one or more embodiments of the invention, in the foregoing description of the embodiments of the present application, multiple features are sometimes merged into one embodiment, figure or description thereof. However, this method of the present application does not mean that the features required for the object of protection are more than the features explicitly stated in each claim. On the contrary, the embodiments of the present invention should have fewer features than the above-mentioned single embodiment.

[0120] In some embodiments, numbers expressing quantity, properties, etc. are used to describe and require some embodiments of the present application, which should be understood to be modified by the terms "about", "approximately" or "substantially" in some cases. Unless otherwise stated, "about", "approximately" or "substantially" indicates that the number is allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which can be changed according to the required characteristics of individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the general method of retaining digits. Although the numerical domains and parameters used to confirm the breadth of their range in some embodiments of the present application are approximate values, in specific embodiments, the setting of such numerical values ​​is as accurate as possible within the feasible range.

[0121] All patents, patent applications, patent application publications, and other materials (such as papers, books, specifications, publications, records, things, and / or the like) referred to herein are hereby incorporated by reference in their entirety for all purposes, except any prosecution record related to such documents, any such documents that are inconsistent or conflicting with this document, or any such documents that have the effect of limiting the broad scope of the claims that may or may not be related to this document. For example, if there is any inconsistency or conflict between the description, definition, and / or use of terms associated with any incorporated material and the terminology associated with this document, the description, definition, and / or terminology used in this document shall control.

[0122] Finally, it should be understood that the embodiments described in this application are only used to illustrate the principles of the embodiments of the present application. Other variations may also fall within the scope of the present application. Therefore, as an example and not a limitation, the alternative configurations of the embodiments of the present application may be considered to be consistent with the teachings of the present application. Accordingly, the embodiments of the present application are not limited to the embodiments explicitly introduced and described in the present application.

Claims

1. A system comprising: at least one storage device including a set of instructions; as well as At least one processor is configured to communicate with the at least one storage device, wherein when executing the set of instructions, the at least one processor is configured to instruct the system to perform operations including: causing a scanning device to perform one or more scans on the object; Based on the one or more scans, obtaining scan data of the object; generating one or more images of the object based on the scan data; and generating a diagnosis result based on the one or more images, the diagnosis result at least indicating whether one or more suspected lesions exist in the object; the diagnosis result indicates lesion information, the lesion information including the severity of the one or more suspected lesions; assigning a label associated with the severity to the diagnosis; The one or more images and / or the diagnosis results are transmitted to a target remote device via a network, the target remote device comprising an image archiving and communication system, and the tags enable the target remote device to sort the diagnosis results according to the severity.

2. The system according to claim 1, characterized in that The diagnostic results are generated based on a machine learning model.

3. The system according to claim 1, characterized in that The lesion information includes at least one of the type of the one or more suspected lesions, the size of the one or more suspected lesions, the location of the one or more suspected lesions, the morphology of the one or more suspected lesions, the symptoms of the one or more suspected lesions, the physiological information of the one or more suspected lesions, or recommendations for subsequent treatment related to the one or more suspected lesions.

4. The system according to claim 1, characterized in that The operations also include: determining whether the severity of the one or more suspected lesions is greater than a threshold; and In response to determining that the severity of the one or more suspected lesions is greater than the threshold, a message is generated indicating that the subject requires priority treatment.

5. The system according to claim 4, characterized in that The operations further include: A notification is sent to the remote surgical device via the network indicating that the subject requires priority treatment.

6. The system according to claim 1, characterized in that The target remote device includes a post-processing workstation.

7. The system according to claim 1, characterized in that The operations further include: The one or more images and the diagnosis result are caused to be displayed.

8. The system according to claim 1, characterized in that The operations further include: Instructions are sent to a remote assistance device to instruct the remote assistance device to schedule a subsequent treatment associated with the subject based on the diagnosis result.

9. The system according to claim 8, characterized in that The remote assistance device includes at least one of a hospital information system, a laboratory information system, a radiology information system, a physician workstation, or a nurse workstation.

10. The system according to claim 1, characterized in that The at least one processor is configured to allow one or more user devices to access the at least one processor via a network to view the one or more images and the diagnosis result.

11. The system according to claim 10, characterized in that Based on the one or more images and / or the diagnostic results, a modification of the scanning parameters of the one or more scans, the reconstruction parameters for generating the one or more images, or at least one of the diagnostic results is performed online by a first user device among the one or more user devices.

12. The system according to claim 11, characterized in that The modification can be viewed in real time through a second user device among the one or more user devices.

13. The system according to claim 10, characterized in that One of the one or more user devices is associated with a physician or an imaging technician.

14. A non-transitory computer readable medium comprising at least one set of instructions, characterized in that: When executed by one or more processors of a computing device, the at least one set of commands causes the computing device to perform a method comprising: causing a scanning device to perform one or more scans on the object; Based on the one or more scans, obtaining scan data of the object; generating one or more images of the object based on the scan data; and generating a diagnosis result based on the one or more images, the diagnosis result at least indicating whether one or more suspected lesions exist in the object; the diagnosis result indicates lesion information, the lesion information including the severity of the one or more suspected lesions; assigning a label associated with the severity to the diagnosis; The one or more images and the diagnosis results are sent to a target remote device via a network, the target remote device comprising an image archiving and communication system, and the tags enable the target remote device to sort the diagnosis results according to the severity.

15. The non-transitory computer readable medium of claim 14, wherein: The diagnostic results are generated based on a machine learning model.

16. The non-transitory computer readable medium of claim 14, wherein: The lesion information includes at least one of the type of the one or more suspected lesions, the size of the one or more suspected lesions, the location of the one or more suspected lesions, the morphology of the one or more suspected lesions, the symptoms of the one or more suspected lesions, the physiological information of the one or more suspected lesions, or recommendations for subsequent treatment related to the one or more suspected lesions.

17. The non-transitory computer readable medium of claim 14, wherein: The method further comprises: determining whether the severity of the one or more suspected lesions is greater than a threshold; and In response to determining that the severity of the one or more suspected lesions is greater than the threshold, a message is generated indicating that the subject requires priority treatment.

18. The non-transitory computer readable medium of claim 17, wherein: The method further comprises: A notification is sent to the remote surgical device via the network indicating that the subject requires priority treatment.

19. The non-transitory computer readable medium of claim 14, wherein: The target remote device includes a post-processing workstation.

20. The non-transitory computer readable medium of claim 14, further comprising: The one or more images and diagnostic results are caused to be displayed.

21. The non-transitory computer readable medium of claim 14, further comprising: Instructions are sent to a remote assistance device to instruct the remote assistance device to schedule a subsequent treatment associated with the subject based on the diagnosis result.

22. The non-transitory computer readable medium of claim 21, wherein: The remote assistance device includes at least one of a hospital information system, a laboratory information system, a radiology information system, a physician workstation, or a nurse workstation.

23. The non-transitory computer readable medium of claim 14, wherein: The one or more processors are configured to allow one or more user devices to access the one or more processors via a network to view the one or more images and the diagnosis result.

24. The non-transitory computer readable medium of claim 23, wherein: Based on the one or more images and / or the diagnostic results, a modification of the scanning parameters of the one or more scans, the reconstruction parameters for generating the one or more images, or at least one of the diagnostic results is performed online by a first user device among the one or more user devices.

25. The non-transitory computer readable medium of claim 24, wherein: The modification can be viewed in real time through a second user device among the one or more user devices.

26. The non-transitory computer readable medium of claim 23, wherein: One of the one or more user devices is associated with a physician or an imaging technician.

27. A system comprising: A control module configured to cause the scanning device to perform one or more scans on the object; The rebuild module is configured as follows: Based on the one or more scans, obtaining scan data of the object; as well as generating one or more images of the object based on the scan data; as well as a diagnosis module configured to generate a diagnosis result based on the one or more images, the diagnosis result at least indicating whether one or more suspected lesions exist in the object; the diagnosis result indicating lesion information, the lesion information including the severity of the one or more suspected lesions; and assigning a label associated with the severity to the diagnosis result; The input / output module is configured to send the one or more images and the diagnosis results to a target remote device via a network, wherein the target remote device includes an image archiving and communication system, and the tags enable the target remote device to sort the diagnosis results according to the severity.

28. The system according to claim 27, characterized in that The diagnostic results are generated based on a machine learning model.

29. The system according to claim 27, characterized in that The lesion information includes at least one of the type of the one or more suspected lesions, the size of the one or more suspected lesions, the location of the one or more suspected lesions, the morphology of the one or more suspected lesions, the symptoms of the one or more suspected lesions, the physiological information of the one or more suspected lesions, or recommendations for subsequent treatment related to the one or more suspected lesions.

30. The system according to claim 27, characterized in that The diagnostic module is configured to: determining whether the severity of the one or more suspected lesions is greater than a threshold; and In response to determining that the severity of the one or more suspected lesions is greater than the threshold, a message is generated indicating that the subject requires priority treatment.

31. The system of claim 30, further comprising an input / output module configured to: A notification is sent to the remote surgical device via the network indicating that the subject requires priority treatment.

32. The system according to claim 27, characterized in that The target remote device includes a post-processing workstation.

33. The system of claim 27, further comprising an input / output module configured to: The one or more images and diagnostic results are caused to be displayed.

34. The system of claim 27, further comprising an input / output module configured to: Instructions are sent to a remote assistance device to instruct the remote assistance device to schedule a subsequent treatment associated with the subject based on the diagnosis result.

35. The system according to claim 34, characterized in that The remote assistance device includes at least one of a hospital information system, a laboratory information system, a radiology information system, a physician workstation, or a nurse workstation.

36. The system according to claim 27, characterized in that The system is configured to allow one or more user devices to access the at least one processor via a network to view the one or more images and the diagnosis result.

37. The system according to claim 36, characterized in that Based on the one or more images and / or the diagnostic results, a modification of the scanning parameters of the one or more scans, the reconstruction parameters for generating the one or more images, or at least one of the diagnostic results is performed online by a first user device among the one or more user devices.

38. The system according to claim 37, characterized in that The modification can be viewed in real time through a second user device among the one or more user devices.

39. The system according to claim 36, characterized in that One of the one or more user devices is associated with a physician or an imaging technician.

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