Method for accelerating medical image retrieval and image archiving and communication system

Abstract

The present invention is entitled "Method for Accelerating Medical Image Retrieval and Picture Archiving and Communication System". A method includes receiving a medical image and parsing the content to determine medical image information. The method includes applying a priority rule based on the medical image information. The priority rule specifies an image storage location for storing the medical image. The image storage location includes a workstation cache memory and a drive of a local storage system, the drive having a different image access speed that is slower than an access speed of the workstation cache memory. The method includes storing the medical image at the designated image storage location as defined by the priority rule, and retrieving the medical image from the designated image storage location in response to a request to view the medical image at a workstation. The method includes presenting the medical image retrieved from the designated image storage location at a display device of the workstation.

Description

Technical Field

[0001] Certain embodiments relate to caching medical images based on exam priority. More specifically, certain embodiments relate to methods and systems for accelerating medical image retrieval based on exam priority by applying exam priority rules to medical images received at a picture archiving and communication system (PACS) to store the medical images at an appropriate storage drive type at a workstation cache or local storage system. Background Art

[0002] Various medical imaging techniques, such as ultrasound imaging, computed tomography (CT), magnetic resonance imaging (MRI), computed radiography, X-ray, positron emission tomography (PET), etc., can be used to image anatomical structures, such as organs, soft tissues, and bones, within the human body. The medical imaging techniques can be configured to acquire medical images, such as CT images, MRI images, ultrasound images, X-ray images, fluoroscopy images, angiography images, mammography images, breast tomosynthesis images, PET images, single photon emission computed tomography (SPECT) images, endoscopy images, microscopy images, optical coherence tomography (OCT) images, etc. The acquired medical images can be stored at a local storage system of a picture archiving and communication system (PACS) for retrieval and viewing at a workstation. However, medical images may not be easily available for viewing by a radiologist or cardiologist during busy hours during the day, which may be problematic when a patient requires immediate attention, such as an emergency room patient or a patient in a trauma care unit.

[0003] Further limitations and disadvantages of conventional and traditional approaches will become apparent to those skilled in the art by comparing such systems with certain aspects of the present disclosure as set forth in the remainder of this application with reference to the accompanying figures. Summary of the invention

[0004] The present invention provides a system and / or method for accelerating medical image retrieval based on exam priority by applying exam priority rules to medical images received at a picture archiving and communication system (PACS) to store the medical images at an appropriate storage drive type at a workstation cache or local storage system, substantially as shown in at least one of the accompanying drawings and / or described in conjunction therewith, as more fully set forth in the claims.

[0005] These and other advantages, aspects and novel features of the present disclosure, as well as details of illustrated embodiments thereof, will be more fully understood from the following description and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0006] Figure 1is a block diagram of an exemplary medical imaging environment configured to accelerate medical image retrieval based on exam priority, according to various embodiments.

[0007] Figure 2 is a flow chart illustrating exemplary steps that may be used to accelerate medical image retrieval based on exam priority, according to various embodiments. DETAILED DESCRIPTION

[0008] Certain embodiments may exist in a method and system for caching medical images based on exam priority. Various embodiments have the following technical effects: medical image retrieval is accelerated based on exam priority by applying exam priority rules to medical images received at a picture archiving and communication system (PACS) to store the medical images at an appropriate storage drive type at a workstation cache or local storage system. Various aspects of the present disclosure have the technical effect of using artificial intelligence to dynamically update priority rules to detect usage patterns and expected exam needs. Various embodiments have the technical effect of providing an intelligent image caching engine integrated with an artificial intelligence system, which is configured to implement priority rules. Certain embodiments have the technical effect of performing image processing and storage or caching for viewing and diagnosis prior to retrieval.

[0009] When reading in conjunction with the accompanying drawings, the following specific embodiments of the aforementioned invention content and certain embodiments will be better understood. In terms of the scope of the figures of the functional blocks of various embodiments shown in the accompanying drawings, these functional blocks do not necessarily represent the division between hardware circuits. Therefore, for example, one or more functional blocks (e.g., processors or memories) can be implemented in a single piece of hardware (e.g., a general signal processor or random access memory block, a hard disk, etc.) or multiple pieces of hardware. Similarly, a program can be an independent program, can be included in an operating system as a subroutine, can be a function in an installed software package, etc. It should be understood that various embodiments are not limited to the arrangements and tools shown in the accompanying drawings. It should also be understood that embodiments can be combined, or other embodiments can be utilized, and structural, logical and electrical changes can be made without departing from the scope of various embodiments. Therefore, the following detailed description should not be considered as a restrictive meaning, and the scope of the present disclosure is limited by the attached claims and their equivalents.

[0010] As used herein, elements or steps listed in the singular and beginning with the word "one" or "an" should be understood not to exclude a plurality of said elements or steps, unless such exclusion is expressly stated. In addition, references to "exemplary embodiments," "various embodiments," "certain embodiments," "representative embodiments," etc. are not intended to be interpreted as excluding the presence of additional embodiments that also incorporate the features of the narration. In addition, unless expressly stated to the contrary, embodiments that "comprise," "include," or "have" an element or multiple elements having a particular attribute may include additional elements that do not have that attribute.

[0011] Furthermore, as used herein, the term processor or processing unit refers to any type of processing unit, whether single-core or multi-core, that can perform the required computations required by various embodiments: CPU, accelerated processing unit (APU), graphics processing unit (GPU), DSP, FPGA, ASIC, or a combination thereof.

[0012] Figure 1 is a block diagram of an exemplary medical imaging environment 100 configured to accelerate medical image retrieval based on exam priority according to various embodiments. Figure 1 , a system 100 is shown, which includes one or more image sources 110 and a picture archiving and communication system (PACS) 120.

[0013] The image sources 110 may include imaging modalities 112, 114 at different locations within a medical imaging site, such as a hospital, and / or medical images from external third parties 116, such as different hospitals, doctors' offices, etc. For example, the different locations within the medical imaging site may include an emergency room and / or trauma unit 112 of a hospital, a medical imaging unit for a planned or scheduled examination 114 of a hospital, a radiology unit, a cardiology unit, an obstetrics unit, and / or any suitable location at the medical imaging site. The imaging modalities may include ultrasound, computed tomography (CT), magnetic resonance imaging (MRI), computed radiography, X-ray, positron emission tomography (PET), and / or any suitable medical imaging modality. The medical images acquired by the imaging modalities 112, 114, and / or third party images 116 may be DICOM files having a header and image data. The medical images may be provided from the image source 110 to a PACS 120 communicatively coupled to the image source 110.

[0014] The PACS 120 may include an acquisition device 121, an intelligent image cache engine 122, priority rules 123, an image processor 124, a local storage system 125, and one or more workstations 130. The acquisition device 121 may include suitable logic, circuitry, interfaces, and / or code configured to receive medical images from the image source 110. The acquisition device 121 may be configured to provide the received medical images to the intelligent image cache engine 122.

[0015] The intelligent image cache engine 122 may be one or more central processing units, microprocessors, microcontrollers, etc. For example, the intelligent image cache engine 122 may be an integrated component, or may be distributed in various locations. The intelligent image cache engine 122 may be capable of receiving image retrievals from the workstation 130 and / or processing requests from the workstation, receiving medical images from the capture device 121, the local storage system 125, the image processor 124, and / or the workstation 130, parsing the content of the medical images, and routing the medical images to the image processor 124, the local storage system 125, and / or the workstation cache memory 134, etc. The intelligent image cache engine 122 may be capable of executing, for example, any of the methods and / or instruction sets discussed herein according to various embodiments.

[0016] The intelligent image cache engine 122 may include suitable logic, circuitry, interfaces, and / or code configured to automatically parse the content of a received medical image to determine medical image information. For example, the intelligent image cache engine 122 may be configured to determine the location or type of image source 110, such as images from an ER / trauma imaging modality 112, images from a planned or ordered imaging exam 114, images from an external or third-party source 116, and the like. As other examples, the intelligent image cache engine 122 may be configured to determine the imaging modality type (e.g., ultrasound, CT, MRI, CR, X-ray, PET, etc.), image type (e.g., two-dimensional (2D), three-dimensional (3D), etc.), exam procedure description (e.g., screening mammogram, diagnostic mammogram, head scan, chest scan, arm fracture, etc.), and / or any suitable medical image information. The intelligent image cache engine 122 may retrieve the priority rules 123 from any suitable data storage medium and apply the priority rules 123 to route the image data to the appropriate storage and / or processing location. For example, the priority rules 123 may prioritize images based on image source 110 location, examination procedure type, image type, and / or any suitable image information or combination of information.

[0017] Priority rules 123 may be arranged in a lookup table (LUT) or as any suitable set of rules. Priority rules 123 may be user defined and / or dynamically created, removed, and / or modified based on patterns of user interaction with medical images detected by artificial intelligence. Priority rules 123 may prioritize the location or type of certain image sources 110 over the location or type of other image sources 110. For example, priority rules 123 may specify that medical images from ER / trauma imaging modalities 112 (e.g., located in an emergency room or trauma center) are the highest priority provided to a cache memory 134 (e.g., the fastest option) of a particular ER workstation 130 to speed up retrieval and viewing of the medical images. Priority rules 123 may specify that medical images from imaging modalities corresponding to planned or ordered imaging examinations 114 (e.g., inpatient departments, outpatient departments, cardiology departments, radiology departments, etc.) have the second highest priority and are provided to a fast solid state drive (SSD) 126 (e.g., the second fastest option) or SSD 127 (e.g., the third fastest option) of a local storage system 125. Priority rules 123 may specify that third-party medical images 116 from external sources (eg, other hospitals or doctors' offices) are associated with the lowest priority and provided to a hard disk drive (HDD) 128 of a local storage system 125 (eg, the slowest option).

[0018] The priority rules 123 may prioritize certain exam procedure types over other exam procedure types. For example, the priority rules 123 may specify that head CT scan images from an ER / trauma imaging modality 112 are the highest priority provided to a cache memory (e.g., the fastest option) of a particular ER workstation 130 to expedite retrieval and viewing of medical images. The priority rules 123 may specify that mammogram screening images from an imaging modality corresponding to a planned or ordered imaging exam 114 have the second highest priority and are provided to a fast solid state drive (SSD) 126 of a local storage system 125 (e.g., the second fastest option). The priority rules 123 may specify that diagnostic mammogram images from an imaging modality corresponding to a planned or ordered imaging exam 114 have the third highest priority and are provided to an SSD 127 of a local storage system 125 (e.g., the third fastest option). Priority rules 123 may specify that computed radiography or X-ray images from external source 116 are associated with the lowest priority and provided to hard disk drive (HDD) 128 of local storage system 125 (eg, the slowest option).

[0019] Priority rules 123 may prioritize certain image types over other image types. For example, priority rules 123 may specify that 3D images are prioritized for 3D reconstruction at image processor 124 of PACS 120, after which the processed images are stored in an appropriate location, such as a fast SSD 126, SSD 127, or HDD 128 of a workstation cache 134 or local storage system 125. Although several examples of priority rules 123 are provided, priority rules may be defined by a user and / or artificial intelligence to prioritize images based on any suitable image information or combination of different image information. Intelligent image cache 122 may be configured to determine image information by parsing the content of an image received via capture device 121.

[0020] The intelligent image cache engine 122 may include suitable logic, circuitry, interfaces and / or code operable to evaluate user interactions with medical images to dynamically update (i.e., add, remove and / or modify) the priority rules 123 stored at the data storage medium of the PACS 120. The intelligent image cache engine 122 may receive user interaction information from one or more workstations 130. The user interaction information may include image retrieval requests and image processing requests, etc. In this regard, for example, the intelligent image cache engine 122 may include an artificial intelligence pattern recognition algorithm and / or a machine learning processing function configured to detect user interaction patterns and update the priority rules 123 in anticipation of examination needs. Additionally and / or alternatively, the artificial intelligence pattern recognition technology or machine learning processing function configured to dynamically update the priority rules 123 may be provided by different processors or distributed on multiple processors at the PACS 120 and / or distributed on remote processors communicatively coupled to the PACS 120. For example, the pattern recognition function may be provided as a deep neural network, which may be composed of, for example, an input layer, an output layer, and one or more hidden layers between the input layer and the output layer. Each layer may be composed of multiple processing nodes, which may be referred to as neurons. For example, a pattern recognition function may include an input layer having a neuron for each user interaction type. The output layer may have neurons corresponding to multiple priority rules. Each neuron of each layer may perform a processing function and pass the processed image interaction information to one of the multiple neurons in the downstream layer for further processing. For example, the neurons of the first layer may learn to recognize patterns regarding image processing requests from different image types. The neurons of the second layer may learn to recognize patterns regarding the timing of image retrieval requests from different image sources. The neurons of the third layer may learn to recognize patterns of image retrieval requests from different inspection procedures based on the detected timing patterns from the second layer. The processing performed by the deep neural network may provide updated priority rules that predict the needs of the inspection with a high degree of probability.

[0021] The image processor 124 may be one or more central processing units, microprocessors, microcontrollers, servers, etc. For example, the image processor 124 may be an integrated component, or may be distributed at various locations. The image processor 124 may be capable of executing software applications, receiving input information from the workstation 130, and generating output for display at the workstation 130 and / or storage at the workstation cache 134 or local storage system 125, etc. The image processor 124 may be capable of executing any image processing instruction set. For example, the image processor 124 may receive a medical image from the intelligent image cache engine 122 and / or the workstation 130, and perform 3D reconstruction and / or other post-processing algorithms on the received medical image in response to instructions received from the intelligent image cache engine 122 and / or the workstation 130.

[0022] The local storage system 125 may include a plurality of data storage media with various access speeds. The local storage system 125 may include a fast SSD 126, an SSD 127, an HDD 128, and / or any suitable data storage media. For example, the local storage system 125 may include a fast SSD 126 with the fastest access speed, an SSD 127 with the second fastest access speed, and an HDD 128 with the third fastest access speed. The local storage system 125 may include a plurality of one or more of the fast SSD 126, the SSD 127, and / or the HDD 128. Additionally and / or alternatively, the local storage system 125 may include additional data storage media, such as a low revolutions per minute (RPM) HDD with the fourth fastest access speed and / or a tape or optical drive with the slowest access speed. The local storage system 125 may be configured to store medical images received from the intelligent image cache engine 122 for subsequent retrieval by the workstation 130.

[0023] Communications between image sources 110 and PACS 120 and / or between components of PACS 120 may be via any one or more types of known networks, including a local area network ("LAN"), a wide area network ("WAN"), an intranet, or a global network (e.g., the Internet). Any of the components of PACS 120 and / or image sources 110 may be coupled to one another via multiple networks (e.g., an intranet and the Internet), such that not all components of system 100 need to be coupled to one another via the same network. Any of image sources 110 and / or components of PACS 120 may be connected to a network or to one another in a wired or wireless manner.

[0024] Still see Figure 1, one or more workstations 130 may communicate with the intelligent image cache engine 122, the image processor 124, and / or at least one other workstation 130. The workstation 130 may be directly attached to the intelligent image cache engine 122 and / or communicate with the intelligent image cache engine 122 via one or more networks. The workstation 130 may be located in a single physical location or in multiple locations. For example, Figure 1 As shown, the workstation 130 may include one or more emergency room workstations, one or more mammogram workstations, and / or one or more reading room workstations. In various embodiments, one or more of the workstations 130 may be a remote workstation. The workstation 130 may be connected to one or more networks and communicate via one or more networks by any suitable combination of wired or wireless data communication links. Each workstation 130 may be implemented using a dedicated or general-purpose computer that executes a computer program for requesting, viewing, manipulating, and / or storing medical images. For example, the workstation 130 may be a personal computer or a terminal attached to a host. For example, the workstation 130 may be any one of a desktop computer, a laptop computer, a notebook computer, a netbook computer, a tablet computer, a mobile phone, or any other electronic device having the ability to access a network.

[0025] In various embodiments, the workstation 130 includes a processor 132, a storage medium 134, an input device 136, and an output device 138, among others. The components of the workstation 130 may be implemented in software, hardware, firmware, and the like. The various components of the workstation 130 may be communicatively linked. The components of the workstation 130 may be implemented separately and / or integrated in various forms. For example, the output device 138 (such as a display) and the input device 136 may be integrated into a touch screen display.

[0026] For example, input device 136 may include any device capable of transmitting information from a user and / or at the user's direction to processor 132 of workstation 130. Input device 136 may include buttons, touch screens, motion tracking, voice recognition, mouse devices, keyboards, styluses, cameras, and / or any other device capable of receiving user instructions. In certain embodiments, for example, one or more of input devices 136 may be integrated into other components such as display output device 138. For example, input device 136 may include a touch screen display.

[0027] Output device 138 may be any device capable of transmitting information to a user. For example, output device 138 may be a display, a printer, and / or a speaker, etc. Display output device 138 may include a liquid crystal display, a light emitting diode display, and / or any suitable display. Display output device 138 may be operable to display information, such as medical images received or retrieved from cache memory 134, intelligent image cache engine 122, local storage system 125, image processor 124, etc.

[0028] The processor 132 may be one or more central processing units, microprocessors, microcontrollers, and the like. For example, the processor 132 may be an integrated component, or may be distributed at various locations. The processor 132 may be capable of executing software applications, receiving input information from the user input device 136, and generating output that may be displayed by the display output device 138, etc. In certain embodiments, for example, the processor 132 may execute an image viewer, retrieve medical images stored to the workstation cache 134, transmit a request for image retrieval from the local storage system 125, and / or transmit a request for processing at the image processor 124. In various embodiments, information provided to the processor 132 by the user input device 136 may be processed by the processor 132 to retrieve medical images from the workstation cache 134, request image retrieval from the local storage system 125, request image processing by the image processor 124, and / or view, manipulate, annotate, and / or request storage of medical images.

[0029] Still see Figure 1For example, the storage medium 134 may be one or more computer-readable memories, such as cache memory (e.g., static random access memory), a hard disk, a floppy disk, a CD, a CD-ROM, a DVD, a compact storage device, a flash memory, a dynamic random access memory, a read-only memory, an electrically erasable and programmable read-only memory, and / or any suitable memory. The storage medium 134 may include, for example, a database, a library, an information set, or other storage device that is accessed by and / or coupled to the processor 132. For example, the storage medium 134 may be capable of temporarily or permanently storing data. The storage medium 134 may be capable of storing data generated by the processor 132 and / or instructions readable by the processor 132, etc. The storage medium 134 may be included in the workstation 130 or physically away from the workstation 130. For example, the storage medium 134 may be accessed by the workstation 130 via a wired or wireless network connection. In various embodiments, the storage medium 134 stores one or more instruction sets of a computer. The instruction set may include one or more routines that can be run or executed by the workstation 130. The instruction set may be embodied in one or more software applications or in computer code. In a representative embodiment, the storage medium 134 includes a cache memory that can receive and store high priority medical images provided by the intelligent image cache engine 122 to speed up retrieval and viewing of the medical images at the display device 138 of the workstation 130 .

[0030] Figure 2 is a flow chart 200 illustrating exemplary steps 202-224 that may be used to accelerate medical image retrieval based on exam priority, according to various embodiments. Figure 2 , a flowchart 200 including exemplary steps 202 to 224 is shown. Certain embodiments may omit one or more steps, and / or perform the steps in a different order than listed, and / or combine certain steps discussed below. For example, some steps may not be performed in certain embodiments. For another example, certain steps may be performed in a different time sequence than listed below, including simultaneously.

[0031] At step 202, medical images are acquired with imaging modalities 112, 114. For example, the images may be acquired by computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, X-ray, fluoroscopy, angiography, mammography, breast tomosynthesis, positron emission tomography (PET), single photon emission computed tomography (SPECT), endoscopy, microscopy, optical coherence tomography (OCT), and / or a suitable imaging modality. An imaging modality may be provided at a hospital, such as an ER / trauma imaging modality 112 or a planning imaging modality 114. The planning imaging modality 114 may be located at an inpatient department, an outpatient department, a cardiology department, a radiology department, an obstetrics department, and / or any suitable department of a hospital. For example, the imaging modality may be a remote imaging modality, such as at a different hospital or a doctor's office.

[0032] At step 204, the medical image is received at the PACS 120. For example, the medical image acquired at step 202 may be transmitted to the capture device 121 of the PACS 120. The capture device 121 may be configured to receive the medical image from the imaging modalities 112, 114 and / or the third party images 116, and provide the medical image to the intelligent image cache engine 122 of the PACS 120.

[0033] At step 206, the intelligent image cache engine 122 of the PACS 120 may automatically parse the content of the medical image to determine the medical image information. For example, the intelligent image cache engine 122 may parse the medical image content to determine the location or type of the image source 110, the imaging modality type, the image type, the examination procedure description, and / or any suitable medical image information. For example, the image source location or type information may be an image from an ER / trauma imaging modality 112, an image from a planned or ordered imaging exam 114, or an image from an external or third party source 116, etc. For example, the imaging modality type may be ultrasound, CT, MRI, CR, X-ray, PET, etc. For example, the image type may be 2D, 3D, 4D, or any suitable image type. For example, the examination procedure description may be screening mammogram, diagnostic mammogram, head scan, chest scan, arm fracture, or any suitable examination procedure description.

[0034] At step 208, the intelligent image cache engine 122 may automatically apply the priority rules 123 based on the determined medical image information. For example, the intelligent image cache engine 122 may apply the priority rules 123 to route the image data to the appropriate storage and / or processing location. For example, the priority rules 123 may prioritize the images based on the image source 110 location, the examination procedure type, the image type, and / or any suitable image information or combination of information parsed from the medical image content at step 206. The priority rules 123 may be provided as a lookup table (LUT) or any suitable set of rules. The priority rules 123 may be user defined and / or dynamically updated based on user interaction patterns with the medical image detected by the artificial intelligence.

[0035] At step 210, the intelligent image cache engine 122 may determine whether the priority rules 123 specify that image processing should be performed on the medical image. For example, the priority rules 123 may specify that a particular image type, an image from a particular examination procedure type, an image from a particular imaging modality, and / or a combination thereof, undergo image processing prior to storage. For example, a 3D image may be prioritized based on the priority rules 123 for 3D reconstruction at the image processor 124 of the PACS 120, after which the processed image is stored at an appropriate location.

[0036] At step 212, if the intelligent image cache engine 122 determines that image processing should be performed, the image processor 124 of the PACS 120 may process the medical image as defined by the priority rules 123. For example, according to the priority rules 123 as determined at step 210, a 3D image may be provided to and post-processed by the image processor 124.

[0037] At step 214, the intelligent image cache engine 122 determines whether the priority rules 123 specify that the medical images should be stored at the cache memory 134 of the workstation 130. For example, the priority rules 123 may specify that medical images from an ER or trauma center imaging modality 112 are given the highest priority (e.g., STAT). The priority rules 123 may be user customizable based on the needs of the system 100. Additionally and / or alternatively, the priority rules 123 may be customizable based on the needs of the system 100 as detected by artificial intelligence.

[0038] At step 216, if the intelligent image cache engine 122 determines that the medical image should be stored at the cache memory 134 of the workstation 130, the intelligent image cache engine 122 provides the medical image to the appropriate workstation cache 134 based on the priority rules 134. For example, the intelligent image cache engine 122 may determine, based on the priority rules executed at step 214, that the medical image is to be stored at a particular workstation 130 in an ER unit or trauma center as defined by the priority rules 123. High priority medical images may be provided to the cache memory 134 of a particular workstation 130 based on the priority rules 123 so that the medical image may be retrieved on an accelerated basis at that workstation 130. In some cases, accelerating the retrieval of medical images from the cache memory 134 may reduce the time for displaying the image at the display device 138 of the workstation 130 by several minutes, which may be critical in typical emergency situations in ERs and trauma centers.

[0039] At step 218, if the intelligent image cache engine 122 determines that the medical image should not be stored at the cache memory 134 of the workstation 130, the intelligent image cache engine 122 provides the medical image to an appropriate storage drive 126, 127, 128 at the local storage system 125. For example, the intelligent image cache engine 122 may store the medical image at one of the plurality of storage drives 126, 127, 128 as defined by the priority rules 123. The storage drives 126, 127, 128 may include drives with different access speeds, such as fast SSD 126, SSD 127, and HDD 128. Medical images with higher priority as defined by the priority rules (such as examination procedure types (e.g., mammogram screening) when a radiologist, cardiologist, etc. is reviewing a waiting patient's medical image) may be stored at a drive (e.g., fast SSD 126) with a faster access time. In contrast, medical images received from third-party image sources 116 (e.g., an x-ray of a broken bone received from a doctor's office) may be stored at a drive with a slower access time (e.g., HDD 128). Medical images provided by live imaging modalities 114 for non-waiting patients or less urgent viewing (e.g., diagnostic mammograms or chest CT scans) may be stored at drives with intermediate access times (e.g., SSD 127). Priority rules 123 may be user customizable based on the needs of system 100. Additionally and / or alternatively, priority rules 123 may be customizable based on the needs of system 100 as detected by artificial intelligence.

[0040] At step 220, the intelligent image cache engine 122 may receive a request from the workstation 130 to retrieve a medical image stored at the local storage system 125. For example, a viewing cardiologist or radiologist may request to retrieve a medical image from the local storage system 125 via the user input device 136 of the workstation 130.

[0041] At step 222, the intelligent image cache engine 122 may retrieve the requested medical image in response to the workstation request and provide it to the workstation 130. For example, the intelligent image cache engine 122 may receive a request from the workstation 130 and, in response, retrieve the requested medical image from the appropriate drive 126, 127, 128 of the local storage system 125. The retrieved medical image may be provided by the intelligent image cache engine 122 to the requesting workstation 130 for presentation at the display device 138 of the workstation 130.

[0042] At step 224, the artificial intelligence may evaluate user behavior to dynamically update the priority rules 123. For example, the intelligent image cache engine 122 may evaluate user interactions with medical images to dynamically add, remove, and / or modify (i.e., update) the priority rules 123 stored at the data storage medium of the PACS 120. The intelligent image cache engine 122 may receive user interaction information, such as image retrieval requests, image processing requests, etc., from one or more workstations 130. For example, the intelligent image cache engine 122 may include an artificial intelligence pattern recognition algorithm and / or machine learning processing functionality configured to analyze the received user interaction information to detect patterns. The artificial intelligence of the intelligent image cache engine 122 may update the priority rules 123 to anticipate examination needs based on the detected patterns. For example, if a pattern of receiving requests to retrieve medical images associated with a particular examination procedure type for immediate viewing at a particular workstation is detected, the artificial intelligence of the intelligent image cache engine 122 may modify an existing rule or create a new rule in the priority rules 123 to assign the highest priority to medical images with the particular examination procedure type so that the medical images are provided to the cache memory 134 of the particular workstation 130. For another example, if the artificial intelligence of the intelligent image cache engine 122 detects a pattern of requests from the workstation 130 to post-process a particular image type, imaging modality type, and / or examination procedure type, the artificial intelligence of the intelligent image cache engine 122 may update the priority rules 123 to automatically provide these medical images to the image processor 124 for post-processing and then storage at the local storage system 125.

[0043] Aspects of the present disclosure provide a method 200 and system 100 for accelerating medical image retrieval based on exam priority. According to various embodiments, the method 200 may include receiving 204, by at least one processor 122 of a picture archiving and communication system (PACS) 120, a medical image provided by one of a plurality of image sources 110. The method 200 may include automatically parsing 206, by the at least one processor 122, the content of the medical image to determine medical image information. The method 200 may include automatically applying 208, by the at least one processor 122, a priority rule 123 based on the determined medical image information. The priority rule 123 may specify one of a plurality of image storage locations 126, 127, 128, 134 for storing the medical image. At least one of the plurality of image storage locations 126, 127, 128, 134 may be a workstation cache memory 134. At least two of the plurality of image storage locations 126, 127, 128, 134 may be drives 126, 127, 128 of a local storage system 125 of the PACS 120. Each of at least two of the plurality of image storage locations 126, 127, 128, 134 may have a different image access speed that is slower than an access speed of the workstation cache memory 134. The method 200 may include storing 216, 218, by the at least one processor 122, the medical image at a designated one of the plurality of image storage locations 126, 127, 128, 134 as defined by the priority rules 123. The method 200 may include retrieving 222 the medical image from the designated one of the plurality of image storage locations 126, 127, 128, 134 in response to a request to view the medical image at the workstation 130. The method 200 may include presenting 222, at a display device 138 of the workstation 130, the medical image retrieved from the designated one of the plurality of image storage locations 126, 127, 128, 134.

[0044] In a representative embodiment, the medical image information may include one or more of the location or type of the image source, the imaging modality type, the image type, or the examination procedure description. In an exemplary embodiment, the priority rules 123 may be arranged as a lookup table. In various embodiments, the drives 126, 127, 128 of the local storage system 125 may include a plurality of: a fast solid state drive (SSD) 126 having a fast SSD image access speed; an SSD 127 having an SSD image access speed; and a hard disk drive (HDD) 128 having an HDD image access speed. The HDD image access speed may be slower than the SSD image access speed. The SSD image access speed may be slower than the fast SSD image access speed. In certain embodiments, the method 200 may include determining 210 by at least one processor 122 to perform image post-processing on the medical image based on the priority rules 123. The method 200 may include performing 212, by at least one image processor 124, image post-processing on the medical image as defined by the priority rules 123, followed by storing 216, 218 the medical image at a designated one of the plurality of image storage locations 126, 127, 128, 134. In a representative embodiment, the method 200 may include an artificial intelligence evaluation 224 performed by the at least one processor 122 with a user interaction with the medical image to detect a medical image usage pattern. The method 200 may include updating 222, by the artificial intelligence, the priority rules 123 based on the detected medical image usage pattern. In an exemplary embodiment, the user interaction with the medical image may include one or both of an image retrieval request and an image processing request. Updating the priority rules 123 may include adding a new priority rule, removing an existing priority rule, or modifying one or more of one or more of the priority rules 123.

[0045] Various embodiments provide a system 100 for accelerating medical image retrieval based on exam priority. The system 100 may include a picture archiving and communication system (PACS) 120, which includes a plurality of image storage locations 126, 127, 128, 134, at least one processor 122, and a workstation 130. The plurality of image storage locations 126, 127, 128, 134 may include a workstation cache memory 134 and a local storage system 125, the local storage system including at least two drives 126, 127, 128. The at least two drives 126, 127, 128 may have different image access speeds that are slower than the access speed of the workstation cache memory 134. The at least one processor 122 may be configured to receive a medical image provided by one of a plurality of image sources 110. The at least one processor 122 may be configured to automatically parse the content of the medical image to determine medical image information. The at least one processor 122 may be configured to automatically apply a priority rule 123 based on the determined medical image information. The priority rules 123 may specify one of the plurality of image storage locations 126, 127, 128, 134 for storing the medical image. The at least one processor 122 may be configured to store the medical image at the specified one of the plurality of image storage locations 126, 127, 128, 134 as defined by the priority rules 123. The workstation 130 may include a display device 138 and a workstation cache memory 134. The workstation 130 may be configured to receive a request to view the medical image at the display device 138. The workstation 130 may be configured to present the medical image retrieved from the specified one of the plurality of image storage locations 126, 127, 128, 134 at the display device 138.

[0046] In an exemplary embodiment, the medical image information may include one or more of the location or type of the image source, the imaging modality type, the image type, or the examination procedure description. In various embodiments, the at least two drives 126, 127, 128 of the local storage system may include a plurality of: a fast solid state drive (SSD) 126 having a fast SSD image access speed; an SSD 127 having an SSD image access speed; and a hard disk drive (HDD) 128 having an HDD image access speed. The HDD image access speed may be slower than the SSD image access speed. The SSD image access speed may be slower than the fast SSD image access speed. In certain embodiments, at least one processor 122 may be configured to determine to perform image post-processing on the medical image based on the priority rules 123. At least one processor 124 may be configured to perform image post-processing on the medical image as defined by the priority rules 123, and then store the medical image at a designated one of the plurality of image storage locations 126, 127, 128, 134. In a representative embodiment, at least one processor 122 may include artificial intelligence configured to evaluate user interactions with the medical image to detect a medical image usage pattern. At least one processor 122 may update the priority rules 123 based on the detected medical image usage pattern. In an exemplary embodiment, the user interaction with the medical image may include one or both of an image retrieval request and an image processing request. The update of the priority rules 123 may include adding a new priority rule, removing an existing priority rule, or modifying one or more of one or more of the priority rules 123.

[0047] Certain embodiments provide a non-transitory computer readable medium having a computer program stored thereon, the computer program having at least one code segment. The at least one code segment is executable by a machine to cause the machine to perform step 200. Step 200 may include automatically parsing 206 the content of the medical image to determine medical image information. The medical image may be received from one of a plurality of image sources 110 at a picture archiving and communication system (PACS) 120. Step 200 may include automatically applying 208 a priority rule 123 based on the determined medical image information. The priority rule 123 may specify one of a plurality of image storage locations 126, 127, 128, 134 for storing the medical image. At least one of the plurality of image storage locations 126, 127, 128, 134 may be a workstation cache memory 134. At least two of the plurality of image storage locations 126, 127, 128, 134 may be drives 126, 127, 128 of a local storage system 125 of the PACS 120. Each of at least two of the plurality of image storage locations 126, 127, 128 may have a different image access speed that is slower than an access speed of the workstation cache memory 134. Step 200 may include storing 216, 218 the medical image at a designated one of the plurality of image storage locations 126, 127, 128, 134 as defined by the priority rules 123. Step 200 may include retrieving 216, 222 the medical image for presentation at a display device 138 of the workstation 130. The medical image may be retrieved from the designated one of the plurality of image storage locations 126, 127, 128, 134 in response to a request 220 to view the medical image at the workstation 130.

[0048] In various embodiments, the medical image information may include one or more of the location or type of the image source, the imaging modality type, the image type, or the examination procedure description. In certain embodiments, the priority rules 123 may be arranged as a lookup table. In a representative embodiment, the drives 126, 127, 128 of the local storage system 125 may include a plurality of: a fast solid state drive (SSD) 126 having a fast SSD image access speed; an SSD 127 having an SSD image access speed; and a hard disk drive (HDD) 128 having an HDD image access speed. The HDD image access speed may be slower than the SSD image access speed. The SSD image access speed may be slower than the fast SSD image access speed. In an exemplary embodiment, step 200 may include determining 210 to perform image post-processing on the medical image based on the priority rules 123. Step 200 may include performing 212 image post-processing on the medical image as defined by the priority rules 123, followed by storing 216, 218 the medical image at a specified one of a plurality of image storage locations 126, 127, 128, 134. In various embodiments, step 200 may include evaluating 224, by the artificial intelligence, user interactions with the medical image to detect medical image usage patterns. Step 200 may include updating 224, by the artificial intelligence, the priority rules 123 based on the detected medical image usage patterns. In certain embodiments, the user interactions with the medical image may include one or both of an image retrieval request and an image processing request. Updating 224 the priority rules 123 may include adding a new priority rule, removing an existing priority rule, or modifying one or more of one or more of the priority rules 123.

[0049] As used herein, the term "circuit" refers to physical electronic components (i.e., hardware) and any software and / or firmware ("code") that can configure hardware, is executed by hardware, and / or is otherwise associated with hardware. For example, as used herein, when executing one or more first codes, a specific processor and memory may include a first "circuit", and when executing one or more second codes, a specific processor and memory may include a second "circuit". As used herein, "and / or" represents any one or more of the items in the list connected by "and / or". For example, "x and / or y" represents any element in the three-element set {(x), (y), (x, y)}. As another example, "x, y, and / or z" represents any element in the seven-element set {(x), (y), (z), (x, y), (x, z), (y, z), (x, y, z)}. As used herein, the term "exemplary" means used as a non-limiting example, instance, or illustration. As used herein, the terms "eg" and "for example" introduce a list of one or more non-limiting examples, instances, or illustrations. As used herein, a circuit is "operable to" and / or "configured to" perform a function whenever the circuit includes the necessary hardware and code (if necessary) to perform the function, regardless of whether the performance of the function is disabled or not enabled by some user-configurable setting.

[0050] Other embodiments may provide a computer-readable device and / or a non-transitory computer-readable medium, and / or a machine-readable device and / or a non-transitory machine-readable medium, on which a machine code and / or a computer program having at least one code segment executable by a machine and / or a computer is stored, thereby causing the machine and / or the computer to perform the steps for accelerating medical image retrieval based on examination priority as described herein.

[0051] Therefore, the present disclosure may be implemented in hardware, software, or a combination of hardware and software. The present disclosure may be implemented in a centralized manner in at least one computer system, or in a distributed manner, where different elements are distributed across several interconnected computer systems. Any type of computer system or other device suitable for executing the methods described herein is suitable.

[0052] The various embodiments may also be embedded in a computer program product, which comprises all the features enabling the implementation of the methods described herein and which, when loaded into a computer system, is capable of carrying out these methods. A computer program herein refers to any expression of a set of instructions in any language, code or notation, which is intended to cause a system with information processing capabilities to perform specific functions directly or after either or both of the following: a) conversion into another language, code or notation; b) reproduction in a different material form.

[0053] Although the present disclosure has been described with reference to certain embodiments, it will be appreciated by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the scope of the present disclosure. In addition, many modifications may be made to adapt specific circumstances or materials to the teachings of the present disclosure without departing from the scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the specific embodiments disclosed, but the present disclosure will include all embodiments falling within the scope of the appended claims.

Claims

1. A method for accelerating medical image retrieval based on examination priority, comprising: receiving, by at least one processor of the picture archiving and communication system, a medical image provided by one of a plurality of image sources; automatically parsing, by the at least one processor, content of the medical image to determine medical image information; evaluating, by the at least one processor, user interactions with the medical images to detect medical image usage patterns, and updating, by the artificial intelligence, priority rules based on the detected medical image usage patterns, wherein the user interactions with the medical images include one or both of image retrieval requests and image processing requests, and the updating of the priority rules includes one or more of adding new priority rules, removing existing priority rules, or modifying one or more of the priority rules; automatically applying, by the at least one processor, the priority rule based on the determined medical image information, the priority rule specifying one of a plurality of image storage locations for storing the medical image, wherein at least one of the plurality of image storage locations is a workstation cache memory, and wherein at least two of the plurality of image storage locations are drives of a local storage system of the picture archiving and communication system, each of the at least two of the plurality of image storage locations having a different image access speed that is slower than an access speed of the workstation cache memory; storing, by the at least one processor, the medical image at a designated one of the plurality of image storage locations as defined by the priority rule; in response to a request to view the medical image at a workstation, retrieving the medical image from a designated one of the plurality of image storage locations; and The medical image retrieved from the designated one of the plurality of image storage locations is presented at a display device of the workstation. 2 . The method of claim 1 , wherein the medical image information comprises one or more of a location or type of an image source, an imaging modality type, an image type, or an examination procedure description.

3. The method according to claim 1, wherein the drive of the local storage system comprises a plurality of: Fast solid-state drive with fast solid-state drive image access speeds, A solid state drive having a solid state drive image access speed, and Hard disk drives, which have hard disk drive image access speeds, Wherein the hard disk drive image access speed is slower than the solid state drive image access speed, and the solid state drive image access speed is slower than the fast solid state drive image access speed.

4. The method according to claim 1, comprising: determining, by the at least one processor, to perform image post-processing on the medical image based on the priority rule; as well as The image post-processing is performed, by the at least one processor, on the medical image as defined by the priority rules before the medical image is stored at the designated one of the plurality of image storage locations.

5. A picture archiving and communication system comprising: A plurality of image storage locations, the plurality of image storage locations comprising: workstation cache memory; and a local storage system comprising at least two drives having different image access speeds that are slower than an access speed of the workstation cache memory; at least one processor, the at least one processor being configured to: receiving a medical image provided by one of a plurality of image sources; automatically parsing the content of the medical image to determine medical image information; evaluating user interactions with the medical image to detect a medical image usage pattern, and updating priority rules based on the detected medical image usage pattern, wherein the user interactions with the medical image include one or both of an image retrieval request and an image processing request, and the updating of the priority rules includes one or more of adding a new priority rule, removing an existing priority rule, or modifying one or more of the priority rules; automatically applying a priority rule based on the determined medical image information, the priority rule specifying one of the plurality of image storage locations for storing the medical image; and storing the medical image at a designated one of the plurality of image storage locations as defined by the priority rule; and A workstation comprising a display device and a workstation cache memory, wherein the workstation is configured to: receiving a request to view the medical image at the display device; and The medical image retrieved from the designated one of the plurality of image storage locations is presented at the display device. 6 . The system of claim 5 , wherein the medical image information comprises one or more of a location or type of image source, an imaging modality type, an image type, or an examination procedure description.

7. The system of claim 5, wherein the at least two drives of the local storage system include a plurality of: Fast solid-state drive with fast solid-state drive image access speeds, A solid state drive having a solid state drive image access speed, and Hard disk drives, which have hard disk drive image access speeds, Wherein the hard disk drive image access speed is slower than the solid state drive image access speed, and the solid state drive image access speed is slower than the fast solid state drive image access speed.

8. The system of claim 5, wherein the at least one processor is configured to: Determining to perform image post-processing on the medical image based on the priority rule; and The image post-processing is performed on the medical image as defined by the priority rules, and thereafter the medical image is stored at a designated one of the plurality of image storage locations.

9. A non-transitory computer-readable medium having a computer program stored thereon, the computer program having at least one code segment, the at least one code segment being executable by a machine to cause the machine to perform steps comprising: automatically parsing the content of a medical image to determine medical image information, the medical image being received at a picture archiving and communication system from one of a plurality of image sources; evaluating, by the at least one processor, user interactions with the medical images to detect medical image usage patterns, and updating, by the artificial intelligence, priority rules based on the detected medical image usage patterns, wherein the user interactions with the medical images include one or both of image retrieval requests and image processing requests, and the updating of the priority rules includes one or more of adding new priority rules, removing existing priority rules, or modifying one or more of the priority rules; automatically applying a priority rule based on the determined medical image information, the priority rule specifying one of a plurality of image storage locations for storing the medical image, wherein at least one of the plurality of image storage locations is a workstation cache memory, and wherein at least two of the plurality of image storage locations are drives of a local storage system of the picture archiving and communication system, each of the at least two of the plurality of image storage locations having a different image access speed that is slower than an access speed of the workstation cache memory; storing the medical image at a designated one of the plurality of image storage locations as defined by the priority rule; and The medical image is retrieved for presentation at a display device of a workstation, the medical image being retrieved from a designated one of the plurality of image storage locations in response to a request to view the medical image at the workstation.

Images