Method and system for analyzing tissue density

Description

TECHNICAL FIELD

[0001] The present disclosure relates to a method and system for image display and processing, and in particular, relates to a tissue density analysis method and system.BACKGROUND

[0002] With the development of modern computer technology and medical imaging technology, there is an ever-increasing demand for accuracy in the analysis of tissues or lesions in medical imaging. Density analysis based on computed tomography (CT) values has been widely used in the analysis of lesions, such as tumors and nodules, and in the analysis of lung tissues of emphysema patients. The CT value is a unit of measurement for determining the density of certain local tissues or organs in a human body. The CT value quantitatively reflects an absorption rate of X-rays by tissues. When a tissue density analysis is performed, a user needs to divide a target tissue or lesion into multiple segments or multiple intervals according to the CT value, and evaluate the target tissue or lesion according to a proportion of a region corresponding to a CT interval or a CT segment in the target tissue.

[0003] CN101105862A relates to a self-adapting adjustment method for medical image window parameters. US20150235085A1 relates to an image processing apparatus etc. that can precisely recognize multiple regions with density value fluctuation in an image with a simple operation in a process of recognizing a specific region from the image. JP2003102723A relates to a medical image display device and its control method.SUMMARY

[0004] The invention is set out in the appended set of claims.BRIEF DESCRIPTION OF THE DRAWINGS

[0005] In order to illustrate the technical solutions related to the embodiments of the present disclosure, brief introduction of the drawings referred to the description of the embodiments is provided below. Obviously, drawings described below are only some examples or embodiments of the present disclosure. Those having ordinary skills in the art, without further creative efforts, may apply the present disclosure to other similar scenarios according to these drawings. Unless stated otherwise or obvious from the context, the same reference numeral in the drawings refers to the same structure and operation. FIG. 1 is a schematic diagram of an application scenario illustrating a tissue density analysis system according to some embodiments of the present disclosure; FIG. 2 is a schematic diagram of an exemplary system configuration illustrating a tissue density analysis device according to some embodiments of the present disclosure; FIG. 3 is a schematic diagram illustrating an exemplary mobile device for implementing one or more specific systems in the present disclosure according to some embodiments of the present disclosure; FIG. 4 is a schematic diagram illustrating an exemplary tissue density analysis device according to some embodiments of the present disclosure; FIG. 5 is a schematic diagram illustrating an exemplary processing module according to some embodiments of the present disclosure; FIG. 6 is a flowchart illustrating an exemplary process for analyzing tissue density according to some embodiments of the present disclosure; FIG. 7A is a schematic diagram illustrating an exemplary tissue density analysis preset by a system according to some embodiments of the p / 0resent disclosure; FIG. 7B is a schematic diagram illustrating an exemplary tissue density analysis that adds a density segmentation according to some embodiments of the present disclosure; FIG. 7C is a schematic diagram illustrating an exemplary tissue density analysis that deletes a density segmentation according to some embodiments of the present disclosure; and FIG. 8 is a schematic diagram illustrating an exemplary numerical display manner on a CT value bar chart according to some embodiments of the present disclosure. DETAILED DESCRIPTION

[0006] As used in the disclosure and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the content clearly dictates otherwise. The terms "including" and "comprising" are merely meant to include the steps and elements that are specifically identified, and such steps and elements do not constitute an exclusive list, and the method or device is also include other steps or elements. The term "based on" is "based at least in part on." The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment." The relevant definitions of other terms will be given in the description below.

[0007] According to some embodiments of the present disclosure, flow charts are used to illustrate the operations performed by the system. It is to be expressly understood, the operations above or below are or are not implemented in order. Conversely, the operations are performed in inverted order, or simultaneously. Besides, one or more other operations are added to the flow charts, or one or more operations are omitted from the flow charts.

[0008] The present disclosure describes a method of tissue density analysis. A tissue density is divided into one or more CT intervals based on CT values. Distributions of different CT intervals or density intervals in the tissue or lesion to be analyzed are represented by a plurality of charts. By displaying the plurality of charts at the same time, the user sets the density interval of the tissue lesions easily, and obtain the density analysis results intuitively.

[0009] FIG. 1 is a schematic diagram of an application scenario illustrating an exemplary tissue density analysis system according to some embodiments of the present disclosure. As shown in FIG. 1, a tissue density analysis system 100 includes an imaging device 110, a storage device 130, and a tissue density analysis device 120.

[0010] The imaging device 110 generates an image by scanning a target object. The image is a medical image. For example, the image is a head image, a chest image, an abdominal image, a pelvic image, a perineal image, a limb image, a spine image, a vertebra image, or the like. The head image includes a brain image, a skull image, or the like. The chest image includes an entire chest image, a heart image, a breast image, or the like. The abdominal image includes an entire abdominal image, a kidney image, a liver image, a lung image, or the like. The image includes, but not limited to, an omnidirectional digitized image, a digitized tomogram image, a phase contrast map, a computed radiography (CR) image, a multimodal image, or the like. The image is a two-dimensional image or a three-dimensional image. The format of the image includes a JPEG format, a TIFF format, a GIF format, an FPX format, or the like. The image is stored in the storage device 130, or be transmitted to the tissue density analysis device 120 for image processing.

[0011] The storage device 130 stores image and / or information related to the image. The image and the information related to the image is provided by the imaging device 110, the tissue density analysis device 120, or an external device of the tissue density analysis system 100. For example, the storage device 130 stores user input information, information obtained from the network 150, or the like. The information related to the image includes an algorithm, a sample, a model, a parameter for image processing, real-time data during image processing, or the like. The storage device 130 is a hierarchical database, a networked database, or a relational database. The storage device 130 is a local database or a remote database. The storage device 130 or other storage devices in the tissue density analysis system 100 digitizes information and store the digitized information using a storage device that operates electrically, optically, or magnetically. In some embodiments, the storage device 130 or the other storage devices in the tissue density analysis system 100 is a device that uses electrical energy to store information, such as a random-access memory (RAM), a read only memory (ROM), or the like. The random access memory includes, but is not limited to, a decimal counter, a select tube, a delay line memory, a Williams tube, a dynamic random access memory (DRAM), a static random access memory (SRAM), a thyristor random access memory (T-RAM), a zero capacitance random access memory (Z-RAM), or the like, or any combination thereof. The read-only memory includes, but is not limited to, a bubble memory, a magnetic button line memory, a thin film memory, a magnetic plate line memory, a magnetic core memory, a drum memory, an optical disk drive, a hard disk, a magnetic tape, a anon-volatile memory (NVRAM), a phase change memory, a magneto-resistive random storage memory, a ferroelectric random access memory, a non-volatile static random access memory, a programmable read-only memory, a shielded heap read memory, a floating connection gate random access memory, a nano random access memory, a track memory, a variable resistance memory, a programmable metallization unit, or the like, or any combination thereof. In some embodiments, the storage device 130 or the other storage devices in the tissue density analysis system 100 is a device that uses magnetic energy to store information, such as a hard disk, a floppy disk, a magnetic tape, a magnetic core memory, a magnetic bubble memory, a USB flash drive, a memory, or the like. In some embodiments, the storage device 130 or the other storage devices in the tissue density analysis system 100 is a device that optically stores information, such as a CD, a DVD, or the like. In some embodiments, the storage device 130 is a device that stores information using a magneto-optical method, such as a magneto-optical disk, or the like. The access mode of the storage device 130 or other storage devices in the tissue density analysis system 100 is a random storage, a serial access storage, a read-only storage, or the like, or any combination thereof. The storage device 130 or the other storage device in the tissue density analysis system 100 is a non-permanent memory or a permanent memory. The storage device 130 described above is merely an example, and the storage device 130 used in the tissue density analysis system 100 is not limited thereto.

[0012] The storage device 130 is a part of the tissue density analysis device 120, a part of the imaging device 110, or exists independently of the tissue density analysis device 120 and the imaging device 110. In some embodiments, the storage device 130 is connected to other modules or devices in the tissue density analysis system 100 via the network 150. The connections between the storage device 130 and the other modules or devices in the tissue density analysis system 100 includes a wired connection, a wireless connection, or a combination thereof.

[0013] The tissue density analysis device 120 obtains image data from the imaging device 110, and / or the storage device 130. The tissue density analysis device 120 analyzes the obtained image data. The analysis includes a tissue density analysis, an airway analysis, or the like. The tissue density analysis includes a tissue or lesion density display, a tissue or lesion density adjustment, or the like. The tissue density analysis device 120 displays tissue or lesion density analysis data to the user in a variety of forms simultaneously. The forms includes a table, a histogram, a CT value bar chart, or the like. The tissue density analysis device 120 displays the processed image data via a display device, store the processed data in the storage device 130, or transmit the processed data to a device other than the tissue density analysis system 100.

[0014] In some embodiments, the tissue density analysis device 120 includes one or more processors, storages, or the like. For example, the tissue density analysis device 120 includes a central processor (CPU), an application specific integrated circuit (ASIC), a dedicated instruction set processor (ASIP), an image processor (GPU), a physical computing processor (PPU), a digital signal processor (DSP), a field programmable gate array (FPGA), a programmable logic device (PLD), a controller, a micro control unit, a processor, a microprocessor, an advanced RISC machine processor, or the like, or any combination thereof.

[0015] In some embodiments, the tissue density analysis system 100 also includes one or more terminal devices 140. The terminal device 140 performs information interaction with the imaging device 110, the storage device 130, and the tissue density analysis device 120. For example, the terminal device 140 obtains processed image data from the tissue density analysis device 120. In some embodiments, the terminal device 140 obtains image data from the imaging device 110 and transmit the image data to the tissue density analysis device 120 for image processing. The one or more terminal devices 140 include a desktop 140-1, a handset 140-2, a tablet computer 140-3, or the like. The one or more terminal devices 140 include one or more input devices, one or more control panels, or the like. For example, the one or more input devices include a keyboard, a touch screen, a mouse, a voice input device, a scanning device, an information recognition device (such as a human eye recognition system, a fingerprint recognition system, a brain monitoring system, etc.), a remote controller, or the like.

[0016] The tissue density analysis system 100 is connected to the network 150. The network 150 is a wireless network, a mobile network, a wired network, or the like. The wireless network includes a Bluetooth, a WLAN, a Wi-Fi, a WiMax, or the like. The mobile network includes a 2G, a 3G, a 4G, or the like. The wired network includes a local area network (LAN), a wide area network (WANs), a private network, or the like.

[0017] The storage device 130 and the tissue density analysis device 120 in the tissue density analysis system 100 executes operational instructions via a cloud computing platform. The cloud computing platform includes a storage cloud platform based on data storage, a computational cloud platform based on data processing, and an integrated cloud computing platform that combines computing, data storage and data processing. For example, image data generated by the tissue density analysis system 100 is processed or stored by a cloud computing platform.

[0018] It should be noted that the above description of the tissue density analysis system 100 is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure.

[0019] FIG. 2 is a schematic diagram of an exemplary system configuration illustrating a tissue density analysis device according to some embodiments of the present disclosure. As shown in FIG. 2, the tissue density analysis device 120 includes a data bus 210, a processor 220, a read only memory (ROM) 230, a random access memory (RAM) 240, a communication port 250, an input / output port 260, a hard disk 270, and a display 280 connected to the input / output port 260. The connection between hardware in the tissue density analysis device 120 is wired, wireless, or a combination of thereof. The hardware is local, remote, or a combination of thereof.

[0020] The data bus 210 is configured to transfer data and / or information. In some embodiments, hardware in the tissue density analysis device 120 transmits data via the data bus 210. For example, the processor 220 sends data to a storage or other hardware such as the input / output port 260 via the data bus 210. It should be noted that the data is real data, an instruction code, state information, control information. In some embodiments, the data bus 210 is an industry standard (ISA) bus, an extended industry standard (EISA) bus, a video electronic standard (VESA) bus, an external component interconnect standard (PCI) bus, or the like.

[0021] The processor 220 is used for logic operations, data processing, and instruction generation. In some embodiments, the processor 220 obtains data / instructions from an internal storage. The storage includes a read only memory (ROM), a random-access memory (RAM), a cache (not shown in FIG. 2), or the like. In some embodiments, the processor 220 includes a plurality of sub-processors configured to implement different functions of the system.

[0022] The read only memory 230 is used for the power-on self-test of the tissue density analysis device 120, an initialization of each functional module in the tissue density analysis device 120, a driver of the input / output of the tissue density analysis device 120, or the like. In some embodiments, the read only memory includes a programmable read only memory (PROM), a programmable erasable read only memory (EPROM), or the like. The random-access memory 240 is used to store an operating system, an application, data, or the like. In some embodiments, the random-access memory 240 includes a static random-access memory (SRAM), a dynamic random-access memory (DRAM), or the like.

[0023] The communication port 250 is configured to connect the operating system with an external network to implement communications between them. In some embodiments, the communication port 250 includes an FTP port, an HTTP port, or a DNS port. The input / output port 260 is configured to exchange and control data and information between an external device or a circuit and the processor 220. In some embodiments, the input / output port 260 includes a USB port, a PCI port, an IDE port, or the like.

[0024] The hard disk 270 is configured to store information and data generated by the tissue density analysis device 120, or information and data received from outside the tissue density analysis device 120. In some embodiments, the hard disk 270 includes a mechanical hard disk (HDD), a solid-state hard disk (SSD), or a hybrid hard disk (HHD). The display 280 is configured display information and data generated by the tissue density analysis system 100 to the user. In some embodiments, the display 280 includes a physical display, such as a display with a speaker, an LCD display, an LED display, an OLED display, an electronic ink display (E-Ink), or the like.

[0025] FIG. 3 is a schematic diagram illustrating an exemplary mobile device for implementing one or more specific systems in the present disclosure according to some embodiments of the present disclosure. As shown in FIG. 3, the mobile device 300 includes a terminal device 140. In some embodiments, the user receives or transmit information related to the tissue density analysis system 100 via the mobile device 300. The mobile device 300 includes a smartphone, a personal digital assistant (PDA), a tablet computer, a handheld game player, smart glasses, a smart watch, a wearable device, a virtual reality device, a display enhancement device, or the like, or any combination thereof. In some embodiments, the mobile device 300 includes one or more central processors (CPUs) 340, one or more image processors (GPUs) 330, a display 320, a memory 360, one or more communication modules 310, a storage 390, and one or more input / output devices 350. The one or more communication modules 310 is configured in the mobile device 300, or connected to the mobile device 300 as a removable external device. Further, the mobile device 300 also includes a system bus, a controller, or the like. As shown in FIG. 3, the central processor 340 downloads the mobile device operating system (e.g., iOS, Android, Windows Phone, etc.) 370 and one or more applications 380 from the storage 390 into the memory 360. The one or more applications 380 includes a web page or other mobile application software (App) for receiving and transmitting information related to the tissue density analysis system 100. The user obtains or provide information via the input / output device 350. The information is transmitted to the tissue density analysis system 100, or a device unit in the tissue density analysis system 100.

[0026] In some embodiments, the computer hardware platform is used as a hardware platform for one or more components (e.g., the tissue density analysis system 100 and a portion thereof), to implement their functions. The hardware components, the operating systems, and the programming languages are inherently traditional, and those skilled in the art applies these techniques to tissue density analysis. A computer with a user interface is a personal computer (PC), other workstations or terminal devices. A programmed computer serves as a server. Since those skilled in the art are familiar with the structure, programming and general operations of the computer used in the present disclosure, detailed explanations are not repeated herein.

[0027] FIG. 4 is a schematic diagram illustrating an exemplary tissue density analysis device according to some embodiments of the present disclosure. In some embodiments, the tissue density analysis device 120 includes an acquisition module 410, a display module 420, a processing module 430, and a storage module 440. Connections between modules in the tissue density analysis device 120 is wired, wireless, or a combination thereof. The module is local, remote, or a combination thereof.

[0028] The acquisition module 410 is configured to obtain image data. In some embodiments, the acquisition module 410 obtains image data from the imaging device 110, the storage device 130, the storage module 440, or outside of the tissue density analysis system 100. The function of the acquisition module 410 is implemented by the processor 220 in FIG. 2. For example, the acquisition module 410 obtains original image data, digitized image data, an image model, an operational instruction, or the like, from the imaging device 110. As another example, the acquisition module 410 obtains standard tissue density analysis image data, partial tissue density analysis image data, or the like, from the storage device 130 or the storage module 440. As another example, the acquisition module 410 obtains standard tissue density analysis image data, image data that requires tissue density analysis, image data after tissue density analysis, or the like, from outside of the tissue density analysis system 100. In some embodiments, the image data is a head image, a chest image, an abdominal image, a pelvic image, a perineal image, a limb image, a spine image, a vertebral image, or the like, including a lesion tissue. The image data includes, but is not limited to, an omnidirectional digitized image, a digitized tomogram, a phase contrast map, computed radiography (CR) image, a multimodal image, or the like. In the present disclosure, an image including a tissue or a lesion is referred to as a medical image or an image. The image data includes pixel information, a CT value of each point in the image, a volume represented by each point in the image, an initial density interval and a volume distribution of the tissue to be analyzed, or the like. In some embodiments, the acquisition module 410 sends the obtained image data to the display module 420, the processing module 430, or the storage module 440. For example, the acquisition module 410 sends the obtained image data to the display module 420 for display. As another example, the acquisition module 410 sends the obtained image data to the processing module 430 for tissue density analysis or processing. As another example, the acquisition module 410 sends the obtained image data to the storage module 440 for storage. In some embodiments, the acquisition module 410 receives a data acquisition instruction from the processor 220 and complete a corresponding data acquisition operation.

[0029] The display module 420 is configured to display a target tissue or lesion in obtained image data. The function of the display module 420 is implemented by the display 280 in FIG. 2. In some embodiments, the display module 420 displays the medical image of the target tissue and a corresponding CT value bar chart simultaneously. The CT value bar chart represents a range of CT values. In some embodiments, the CT value bar chart includes one or more sliders. The one or more sliders divide the CT values into one or more CT intervals or density segmentations. The one or more CT intervals is represented by one or more color bars or grayscale bars. The color bar is a line segment represented by one color, for example, red, orange, yellow, green, blue, purple, black, white, or the like. The grayscale bar is a line segment represented by black, white, or a transition color from black to white. In some embodiments, the display module 420 displays a medical image of the target tissue, a CT value bar chart, a histogram, and / or a table corresponding to the target tissue, simultaneously. The histogram is associated with the target tissue and the CT value bar chart. The histogram represents a volume distribution of regions having different CT values in the target tissue. The table is associated with the target tissue, the CT value bar and the histogram. The table represents volumes and volume percentages of different CT intervals in the target tissue. In some embodiments, the medical image, the histogram, and the table of the target tissue is divided into one or more regions according to one or more CT intervals of the CT value bar chart. For example, if the CT value bar chart has two CT intervals, the medical image of the target tissue is divided into two regions, the histogram is divided into two parts, and the table is divided into two sets of data. In some embodiments, the display module 420 represents a CT interval in one color. For example, a color of a region representing a CT interval in the medical image, the histogram, and the table of the target tissue is consistent with a color representing the CT interval in the CT value bar chart. Specifically, the color of the data strip in a CT interval in the histogram is consistent with the color of the color bar in the corresponding section in the CT value bar chart. A set of volume data, a set of volume percentage data, and the color of the corresponding CT value in the table is consistent with the color of the color bar in the corresponding section in the CT value bar chart. In some embodiments, the display module 420 represents a background of a displayed page in one or more colors. The colors include, but is not limited to, red, orange, yellow, green, blue, purple, black, white, or the like. For example, the background color of the display page is green. In some embodiments, the display module 420 displays, by one or more arrangements, the medical image of the target tissue and the CT value bar chart, the histogram, and / or the table representing a CT interval distribution on the medical image of the target tissue. The arrangement includes a left-right juxtaposition arrangement (as shown in FIG. 7A), an upper and lower juxtaposition arrangement, a wraparound arrangement centered on the medical image of the target tissue, or the like, or any combination thereof. In some embodiments, the display module 420 displays the image data in one or more languages. The one or more languages include Chinese, English, Japanese, German, or the like. A specific embodiment is described in FIG. 7A. The medical image of the target tissue, the CT value bar chart, the histogram and / or the table representing the CT interval distribution on the medical image of the target tissue is displayed on a same display interface. In some embodiments, the medical image of the target tissue, the CT value bar chart, the histogram, and / or the table representing the CT interval distribution on the medical image of the target tissue is displayed on different display interfaces. In some embodiments, the medical image of the target tissue, the CT value bar chart, the histogram, and / or the table representing the CT interval distribution on the medical image of the target tissue is displayed on different display interfaces in different combinations. In some embodiments, the different display interfaces include a tiled display or an overlapping display.

[0030] The processing module 430 is configured to adjust a density segmentation or a CT interval. The processing module 430 also is configured to determine a volume and a volume percentage of at least one CT interval. In some embodiments, the processing module 430 adjusts the division of the CT interval by adjusting one or more sliders in the CT value bar chart. For example, the processing module 430 modifies one or more CT intervals, adds one or more CT intervals, or deletes one or more CT intervals. In some embodiments, the processing module 430 determines and adjusts image data representing different CT intervals in the histogram and / or the table according to an adjustment result of the CT interval on the CT value bar chart. The image data in the CT value bar chart, the histogram, and / or the table is adjusted or changed simultaneously, such that the data in each chart corresponds to each other. For example, if the CT intervals on the CT value bar chart change from two intervals to three intervals, the processing module 430 divides data in the histogram into three parts, and / or adjust data in the table to three groups. In some embodiments, the processing module 430 determines a volume and a volume percentage corresponding to each section after the CT interval adjustment according to the image data obtained by the acquisition module 410 and the CT value bar chart. The image data includes a CT value of each point in the image, a volume represented by each point in the image, an initial density interval and a volume distribution of the tissue to be analyzed, or the like. In some embodiments, the processing module 430 determines different colors for different CT intervals. The colors include, but are not limited to, red, orange, yellow, green, blue, purple, black, white, or the like. For example, a CT value bar chart have two CT intervals represented by yellow and purple color bars, respectively. When a new CT interval is added in the CT value bar chart, the processing module 430 determines a color different from the colors of the other two CT intervals, e.g., green, for the added CT interval in the CT value bar chart, the histogram, and / or the table. As another example, a CT value bar chart has four CT intervals represented by pink, blue, orange, and white color bars, respectively. The processing module 430 determines other colors for the four CT intervals in the histogram, and / or the table corresponding to the CT value bar chart, e.g., red, gold, purple, and yellow, respectively. In some embodiments, the processing module 430 adjusts the background color of the displayed page. In some embodiments, the processing module 430 adjusts the arrangement of the CT image of the target tissue, the CT value bar chart, the histogram, and / or the table representing the CT interval distribution on the medical image of the target tissue. The arrangement includes a left-right juxtaposition arrangement, an upper and lower juxtaposition arrangement, a wraparound arrangement centered on the medical image of the target tissue, or the like, or any combination thereof. For example, the processing module 430 adjusts the arrangement of the medical image, the CT value bar chart, the histogram, and / or the table from the left-right juxtaposition arrangement to the upper and lower juxtaposition arrangement. The arrangement refers to an arrangement in any order. For example, the CT value bar chart, the medical image, the histogram, and / or the table is arranged from left to right successively. As another example, the table, the histogram, the CT value bar chart, and the medical image is arranged from upper to lower successively. The processing module 430 sends the processed image data to the display module 420 for display, or to the storage module 440 for storage.

[0031] The storage module 440 is configured to store image data or operational instructions. The function of the storage module 440 is implemented by the hard disk 270, the read only memory 230, the random-access memory 240 shown in FIG. 2, or the like, or any combination thereof. The storage module 440 stores image data and / or operation instructions obtained by the acquisition module 410, real time data generated by the processing module 430, processed image data, or the like. The operational instructions include a volume and / or volume percentage algorithm, a permutation algorithm, a color configuration algorithm, or the like. The storage module 440 includes, but not limited to, various types of storage devices such as a solid-state hard disk, a mechanical hard disk, a USB flash memory, an SD memory card, an optical disk, a random-access memory (RAM), or a read only memory (ROM). The storage module 440 is a storage device included in the system, or an external storage device of the system, such as a storage on a cloud storage server.

[0032] It should be noted that the above description of the tissue density analysis device 120 is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications are made under the teachings of the present disclosure. However, those variations and modifications do not depart from the scope of the present disclosure. The modules are combined in any way. The modules form a subsystem and are connected to other modules. For example, the acquisition module 410 and the display module 420 are integrated into a single module.

[0033] FIG. 5 is a schematic diagram illustrating an exemplary processing module according to some embodiments of the present disclosure. In some embodiments, the processing module 430 includes a modification unit 510, an adding unit 520, and a deleting unit 530. The connections between modules in the processing module 430 are wired, wireless, or a combination thereof. The module is local, remote, or a combination thereof.

[0034] The modification unit 510 is configured to modify a density segmentation or a CT interval. In some embodiments, the modification unit 510 modifies the CT interval by moving a slider on the CT value bar chart. For example, the modification unit 510 moves the slider left and right via a mouse, a screen touch, a voice, or the like. In some embodiments, the modification unit 510 modifies the CT interval by modifying the CT value corresponding to the slider on the CT value bar chart. The CT value corresponding to the slider is displayed above the CT value bar chart or the slider. The CT value corresponding to the slider is displayed below the CT value bar chart or the slider. As shown in FIG. 8, the CT value above the CT value bar chart or the slider is reasonably arranged to avoid a layout problem includes threshold information overlaps or a densely arrangement due to a small segmentation or CT interval. For example, the modification unit 510 modifies the CT interval to a new CT interval by clicking or double-clicking the CT value corresponding to a slider on the CT value bar chart and inputting the new CT value. In some embodiments, the modification unit 510 adjusts the CT interval on the CT value bar chart by modifying the CT value or the CT interval in the table. In some embodiments, the modification unit 510 determines and adjusts image data representing different CT intervals in the histogram and / or the table according to the modified CT interval. The image data includes volumes and / or volume percentages, or the like, of different CT intervals in the tissue to be analyzed. In some embodiments, the modification unit 510 adjusts colors of different CT intervals. For example, a CT value bar chart has three CT intervals represented by blue, green, and orange color bars, respectively. The modification unit 510 adjusts the colors of the corresponding three CT intervals in the CT value bar chart, the histogram, and / or the table to white, purple, and gold, respectively. In some embodiments, the modification unit 510 adjusts an arrangement of the medical image of the target tissue, the CT value bar chart, the histogram, and / or the table. For example, the modification unit 510 arranges the CT value bar chart, the histogram, and / or the table in an upper and lower juxtaposition arrangement. The modification unit 510 arranges the medical image of the target tissue, and the CT value bar chart, the histogram, and / or the table in a left-right juxtaposition arrangement. The modification unit 510 adjusts this arrangement to a wraparound arrangement centered on the medical image of the target tissue. The CT value bar chart, the histogram, and the table are arranged on an upper side, a left side, and a right side of the medical image of the target tissue.

[0035] The adding unit 520 is configured to add a density segmentation or a CT interval. In some embodiments, the adding unit 520 adds a CT interval on the CT value bar chart. For example, the adding unit 520 adds a CT interval by clicking or double clicking a point on the CT value bar chart. The adding unit 520 determines a CT value of the CT interval by sliding the slider left and right. As another example, the adding unit 520 clicks or double clicks a point on the CT value bar chart, and modify a CT value corresponding to the point, to add a new CT interval. As another example, the adding unit 520 adds a CT interval by voice. In some embodiments, the adding unit 520 determines and adjust image data representing different CT intervals in the histogram and / or the table based on the adjusted CT intervals. The image data includes volumes and / or volume percentages of different CT intervals in the tissue to be analyzed, or the like. In some embodiments, the adding unit 520 determines a color for a newly added CT interval. For example, a CT value bar chart has two CT intervals represented by orange and blue color bars, respectively. When a new CT interval is added in the CT value bar chart, the adding unit 520 determines a color for the newly added CT interval on the CT value bar chart, the histogram, and / or the table. The color is different from the colors of the two CT intervals, such as white.

[0036] The deleting unit 530 deletes a density segmentation or a CT interval. In some embodiments, the deleting unit 530 deletes one or more CT intervals from the CT value bar chart. For example, the deleting unit 530 deletes a CT segment value corresponding to a slider by moving a slider up and down. Therefore, two CT intervals including the CT segment value are adjusted to one CT interval. The up and down movement is implemented by a mouse, a screen touch, or the like. The CT segment value is any CT value between two endpoints of the CT value bar chart. As another example, the deleting unit 530 deletes one or more CT intervals by modifying a CT segment value to be deleted to a CT segment value to be reserved. As another example, the deleting unit 530 deletes a CT interval by voice. In some embodiments, the deleting unit 530 determines and adjust image data representing different CT intervals in the histogram and / or the table based on the adjusted CT interval. The image data includes volumes and / or volume percentages of different CT intervals in the tissue to be analyzed, or the like. In some embodiments, the deleting unit 530 modifies colors of two intervals including the deleted CT segment value to a same color. The color is any one of the colors of the original two intervals, or is a third color different from the colors of the original two intervals. For example, a CT value bar chart has three CT intervals represented by red, green, and blue color bars, respectively. When a CT segment value is deleted from the CT value bar chart, and the CT segment value is located between the two CT intervals represented by the green and blue color bars respectively, the deleting unit 530 changes the CT intervals represented by the green and blue color bars to a blue color bar. As another example, the deleting unit 530 changes the two CT intervals represented by the green and blue color bars to a new color bar, such as a yellow color bar.

[0037] It should be noted that the above description of the processing module 430 is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications are made under the teachings of the present disclosure. However, those variations and modifications do not depart from the scope of the present disclosure. The modules are combined in any way. The modules form a subsystem and are connected to other modules. For example, the modification unit 510 is further divided into a CT interval modification unit, a color modification unit, an arrangement modification unit, or the like. As another example, the modification unit 510 is integrated with the adding unit 520 or the deleting unit 530.

[0038] FIG. 6 is a flowchart illustrating an exemplary process 600 for analyzing tissue density according to some embodiments of the present disclosure. In 610, the tissue density analysis device 120 obtains tissue density distribution data. The tissue density distribution data includes an image including a tissue to be density-analyzed, a CT value of each point in the image, a volume represented by the each point in the image, an initial density interval and a volume distribution of the tissue to be density-analyzed, or the like. In some embodiments, the tissue density distribution data is obtained by the acquisition module 410. For example, the tissue density distribution data is obtained by the acquisition module 410 via a network transmission, a hardware storage device transmission, or the like.

[0039] In 620, the tissue density analysis device 120 displays the obtained tissue density distribution data in one or more charts. The charts include a medical image, a CT value bar chart, a histogram, a table, or the like. In some embodiments, the obtained tissue density distribution data is displayed by the medical image and the CT value bar chart. Specifically, an image of the tissue or lesion to be analyzed is displayed by the medical image. The medical image is zoomed in or zoomed out. The CT interval of the tissue or lesion to be analyzed is displayed by the CT value bar chart. In some embodiments, the obtained tissue density distribution data is displayed by the medical image, the CT value bar chart, the histogram, and / or the table. Specifically, a lesion volume corresponding to different CT values of the tissue or lesion to be analyzed is displayed by the histogram. The lesion volume and volume percentage corresponding to different CT values or CT intervals of the tissue or lesion to be analyzed are displayed in the table. The volume percentage is determined based on a total volume of the tissue or lesion to be analyzed. In some embodiments, the tissue density analysis device 120 displays one or more charts including the tissue density distribution data in one or more arrangements. For example, the one or more charts are arranged in a left-right juxtaposition arrangement, an upper and lower juxtaposition arrangement, a wraparound arrangement, or the like, or any combination thereof. As shown in FIG. 7A, the CT value bar chart, the histogram, and the table are arranged in an upper and lower juxtaposition arrangement. The CT value bar chart, the histogram, the table, and the medical image are displayed in a left-right juxtaposition arrangement. In some embodiments, the tissue density analysis device 120 displays the background in one or more colors. The display colors of the background include, but not limited to, black, green, pink, white, or the like. In some embodiments, the tissue density analysis device 120 displays colors of different CT intervals in the chart based on the color of the background. The display colors of a same CT interval in different charts are the same. The display color of the CT interval in the chart is different from the display color of the background. For example, if the display color of the background is green, and the CT values has three intervals, the colors of the three CT intervals in the medical image, the CT value bar chart, the histogram, and / or the table are yellow, red, and purple, respectively.

[0040] In 630, the tissue density analysis device 120 processes the tissue density distribution data displayed in the one or more charts. In some embodiments, the tissue density analysis device 120 adjusts the tissue density distribution data by adjusting a density segmentation or a CT interval in the one or more charts. For example, the tissue density analysis device 120 modifies one or more CT intervals, add one or more CT intervals, or delete one or more CT intervals. In some embodiments, the CT interval is adjusted by moving a slider on the CT value bar chart left and right. For example, a slider is located on the CT value bar chart at a position where the CT value is -100, and the slider is moved to a new CT segment value position, for example, -300, via a mouse or a screen touch. In some embodiments, the CT interval is adjusted by moving the slider on the CT value bar chart by voice. In some embodiments, a CT interval is added at any point on the CT value bar chart with click, double click, or voice input. For example, if a CT segment value to be added is -400, a position between two endpoints of the CT value bar chart other than the CT segment value is clicked or double-clicked, to obtain a slider corresponding to the position. The CT value corresponding to the slider is modified to the CT segment value of -400, and a new CT interval is added. Accordingly, a CT interval or a segmentation region is added in the medical image, the histogram, and / or the table. In some embodiments, a CT segment value is deleted by moving the slider on the CT value bar chart up and down, thereby deleting a CT interval. For example, the CT value bar char includes four CT segment values. The four CT segment values include two endpoints of the CT value bar chart, a position corresponding to a CT value of -100, and a position corresponding to a CT value of -500. A CT segment value to be deleted is - 100. A slider corresponding to the CT value of -100 is moved to the top or bottom of the CT value bar chart via a mouse or a screen touch, and the CT segment value of -100 is deleted. The CT intervals on the left and right sides of the segmentation value is combined into one CT interval. In some embodiments, the CT segment value to be deleted is modified to a CT segment value to be reserved, thereby deleting one or more CT intervals. For example, the CT segment value -100 is deleted by modifying the CT segment value from -100 to -500, or a CT value corresponding to an endpoint of the CT value bar chart.

[0041] In some embodiments, the tissue density analysis device 120 determines and adjust image data representing different CT intervals in the histogram and / or the table according to the adjusted CT intervals. For example, a corresponding volume and volume percentage in the histogram and / or the table is redetermined based on the adjusted CT intervals. The volume or the volume percentage is determined based on a CT value of each point in the image obtained by the acquisition module 410, a volume represented by the each point of the image, an initial density interval, a volume distribution of the tissue to be analyzed, or the like. In some embodiments, the tissue density analysis device 120 adjusts the displayed color of the background and / or the colors of different CT intervals in the chart. For example, the display color of the background is green. The CT values have three intervals. The colors of the medical image, the CT value bar chart, the histogram, and / or the table is yellow, green, and purple, respectively. The colors of the three CT intervals is adjusted to orange, red, and white, respectively. As another example, the CT interval represented by green is adjusted to a new color, such as gray. In some embodiments, the tissue density analysis device 120 adjusts the arrangement of the medical image, the CT value bar chart, the histogram, and / or the table of the target tissue. The arrangement includes a left-right juxtaposition method, an upper and lower juxtaposition method, a wraparound arrangement centered on a medical image of the target tissue, or the like. In some embodiments, the tissue density analysis device 120 performs a density analysis on lung tissue, and perform an airway analysis according to divided CT intervals of the lung tissue.

[0042] In 640, the tissue density analysis device 120 displays the processed tissue density distribution data in one or more charts. The processed tissue density distribution data includes tissue density distribution data after density segmentation, CT interval modification, CT interval addition, and / or CT interval deletion, the medical image, a color of the CT value bar chart, the histogram, and / or the table, the tissue density distribution data after arrangement adjustment, the tissue density distribution data after changing the color of the background. Accordingly, the medical image, the CT value bar chart, the histogram and / or the table of the tissue or lesion to be density-analyzed are combined, displayed, and processed. The user sets the density segmentation of the tissue or lesion based on CT values easily, or observe a result of density analysis intuitively.

[0043] It should be noted that the above description of the analysis of the tissue density is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications are made under the teachings of the present disclosure. However, those variations and modifications do not depart from the scope of the present disclosure. For example, operation 620 and operation 630 is performed simultaneously.

[0044] FIG. 7A is a schematic diagram illustrating an exemplary tissue density analysis preset by a system according to some embodiments of the present disclosure. As shown in FIG. 7A, 782 refers to an image including a tissue or lesion, 701 refers to the tissue or lesion in the image 782 for tissue density analysis. As shown in FIG. 7A, 781 refers to a preset tissue density distribution map corresponding to the tissue density analysis region 701. The preset tissue density distribution map 781 includes a CT value bar chart 750, a histogram 760, and a table 770. The CT value bar chart 750 represents CT values of the tissue density analysis region 701. For example, 702 represents a CT value of 0, and 703 represents a CT value of -694. The position of each slider between 702 and 703 represents a density segmentation threshold. For example, 704 represents a density segmentation threshold of -333. 705 and 706 represents a region in which the density value is a CT value between 0 and -333, and a region in which the density value is a CT value between -333 to -694, respectively. 705 and 706 are displayed in different colors. For example, 705 is displayed in green, and 706 is displayed in orange. The histogram 760 represents volumes of different density segmentations in the tissue density analysis region 701. For example, 707 corresponds to 702 in the CT value bar chart 750. An ordinate value of 707 is 0, which indicates that the tissue density analysis region 701 does not include a region with a CT value of 0. 709 corresponds to 703 in the CT value bar chart 750. An ordinate value of 709 is 0, which indicates that the tissue density analysis region 701 does not include a region with a CT value of -694. 708 corresponds to 704 in the CT value bar chart 750. An ordinate value of 708 is about 0.91, which indicates that a volume in the tissue density analysis region 701 with the CT value of -333 is about 0.91 mm 3< . The table 770 represents volumes and volume percentages of different density segmentations in the density analysis region. For example, 710 represents that a volume of a region with CT values between -694 and -333 is 47 mm 3< , and a volume percentage in the tissue density analysis region 701 is 81%. 710 corresponds to 706 in the CT value bar chart 750, and a region between 709 and 708 in the histogram 760. 711 represents that a volume of a region with CT values between -333 and 0 is 11 mm 3< , and a volume percentage in the tissue density analysis region 701 is 19%. 711 corresponds to 705 in the CT value bar chart 750, and a region between 708 and 707 in the histogram 760. The region density analysis region 701 shown in FIG. 7A has two regions with significantly different colors, corresponding to the two density segmentations in the preset density distribution map 781 in FIG. 7B.

[0045] FIG. 7B is a schematic diagram illustrating an exemplary tissue density analysis that adds a density segmentation according to some embodiments of the present disclosure. As shown in FIG. 7B, 782 refers to an image including a tissue or lesion, and 701 refers to the tissue or lesion to be analyzed in the image 782. As shown in FIG. 7B, 781 refers to a tissue density distribution map after adding a density segmentation or a CT interval corresponding to the tissue density analysis region 701. As shown, the CT value bar chart 750 includes four density segmentations, such as, 714, 715, 716, and 717, respectively. Accordingly, the histogram 760 is also divided into four sections. The density segmentation point positions include 707, 720, 718, 719, and 709, respectively. The table 770 is also divided into four parts. 721 represents that a volume of a region with CT values between -694 and -583 is 10 mm 3< , and a volume percentage in the tissue density analysis region 701 is 17%. 721 corresponds to 717 in the CT value bar chart 750, and a region between 709 and 719 in the histogram 760. 722 represents that a volume of a region with CT values between -583 and -333 is 37 mm 3< , and a volume percentage in the tissue density analysis region 701 is 64%. 722 corresponds to 716 in the CT value bar chart 750 and a region between 719 and 718 in the histogram 760. 723 represents that a volume of a region with CT values between -333 and -119 is 11 mm 3< , and a volume percentage in the tissue density analysis region 701 is 19%. 723 corresponds to 715 in the CT value bar chart 750, and a region between 718 and 720 in the histogram 760. 724 represents that the tissue density analysis region 701 does not include a region with CT values between -119 and 0. 724 corresponds to 714 in the CT value bar chart 750, and a region between 720 and 707 in the histogram 760. In some embodiments, the density segmentation is added by clicking a specified point on the CT value bar chart 750 via a mouse. For example, a density segmentation point 713 is added by clicking a position indicating that the CT value is -583 on the CT value bar chart 750. As another example, a density segmentation point 712 is added by clicking a position indicating that the CT value is -119 on the CT value bar chart 750. In some embodiments, a density segmentation is added by clicking any point on the CT value bar chart 750 via a mouse, and modifying the CT value above the point into a CT value of a specified point. For example, a slider with a CT value of -360 on the CT value bar chart 750 is obtained by clicking a point with a CT value of -360. A density segmentation is added at a position with a CT value of -583 by modifying the value above the slider from -360 to -583 via clicking. As another example, a slider with a CT value of -600 on the CT value bar chart 750 is obtained by clicking a point with a CT value of -600. A density segmentation is added at a position with a CT value of -119 by modifying the value above the slider from -600 to -119 via clicking. In some embodiments, by adding the density segmentation on the CT value bar chart 750, the segment regions in the histogram 760 and the table 770 are also changed accordingly. At the same time, a number (or count) of regions in the tissue density analysis region 701 are also increased. For example, according to the density segmentations of the CT value bar chart 750 in FIG. 7B, the tissue density analysis region 701 is divided into four regions. In some embodiments, colors of different density segmentation regions in the tissue density analysis region 701 are the same as colors of different density segmentation regions in the CT value bar chart 750, the histogram 760, and the table 770, and change simultaneously.

[0046] FIG. 7C is a schematic diagram illustrating an exemplary tissue density analysis that deletes a density segmentation according to some embodiments of the present disclosure. As shown in FIG. 7C, 782 refers to an image including a tissue or lesion, and 701 refers to the tissue or lesion in the image 782 to be density-analyzed. As shown in FIG. 7C, 781 refers to a tissue density distribution map corresponding to the tissue density analysis region 701 after one or more density segmentations or CT intervals are deleted in the density segmentation in FIG. 7B. As shown, the CT value bar chart 750 includes three density segmentations, such as 714, 726, and 717, respectively. Accordingly, the histogram 760 is also divided into three parts, with 707, 720, 719, and 709 as density segmentation point positions, respectively. The table 770 is also divided into three parts. 721 represents that a volume of a region with CT values between -694 and -583 is 10 mm 3< , and a volume percentage in the tissue density analysis region 701 is 17%. 721 corresponds to 717 in the CT value bar chart 750 and a region between 709 and 719 in the histogram 760. 727 represents that a volume of a region with CT values between -583 and - 119 is 48 mm 3< , and a volume percentage in the tissue density analysis region 701 is 82%. 727 corresponds to 726 in the CT value bar chart 750, and a region between 713 and 712 in the histogram 760. 728 represents that the tissue density analysis region 701 does not include a region with CT values between -119 and 0. 728 corresponds to 714 in the CT value bar chart 750 and a region between 720 and 707 in the histogram 760. In some embodiments, a density segmentation is deleted by moving the slider up and down. For example, if a slider with the CT value of -333 is the density segmentation value to be deleted, the density segmentations 716 and 715 in FIG. 7B is deleted by moving a slider with the CT value of -333 on the CT value bar chart 750 up and down. In some embodiments, a density segmentation is deleted by modifying a value of the slider to be deleted to a CT value of the density segmentation point to be reserved, or a CT value of a specific density segmentation point. For example, the density segmentation value with a CT value of -333 is deleted by modifying a value above the slider with a CT value of -333 on the CT value bar chart 750 to 0, -119, -583, or -694. A density distribution map is determined, as shown in FIG. 7C. In some embodiments, by deleting the density segmentation on the CT value bar chart 750, the segment regions in the histogram 760 and the table 770 are also be changed accordingly. At the same time, partitions in the tissue density analysis region 701 are also reduced. For example, according to the density segmentation in the CT value bar chart 750 in FIG. 7C, the tissue density analysis region 701 is divided into three regions.

[0047] Having thus described the basic concepts, it may be rather apparent to those skilled in the art after reading this detailed disclosure that the foregoing detailed disclosure is intended to be presented by way of example only and is not limiting. Various alterations, improvements and modifications to the present disclosure may occur and are intended to those skilled in the art, though not explicitly stated herein. These alterations, improvements, and modifications are intended to be suggested by this disclosure, and are within the scope of the exemplary embodiments of this disclosure.

[0048] Moreover, certain terminology has been used to describe embodiments of the present disclosure. For example, the terms "one embodiment," "an embodiment," and / or "some embodiments" mean that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various parts of this specification are not necessarily all referring to the same embodiment. In addition, certain features, structures, or characteristics may be combined as suitable in one or more embodiments of the present disclosure.

[0049] Moreover, it will be appreciated by one skilled in the art, aspects of the present disclosure may be illustrated and described herein in any of a number of patentable classes or context including any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof. Accordingly, various aspects of the present disclosure may be implemented entirely hardware, entirely software (including firmware, resident software, micro-code, etc.), or combining hardware and software. The above hardware or software may be referred to as "data block", "module", "engine", "unit", "component" or "system". Furthermore, aspects of the present disclosure may take the form of a computer program product embodied in one or more computer readable media having computer readable program code embodied thereon.

[0050] A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including electro-magnetic, optical, or the like, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that may communicated, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable signal medium may be transmitted using any appropriate medium, including wireless, wireline, optical fiber cable, RF, or the like, or any suitable combination of the foregoing.

[0051] Computer program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB. NET, Python, or the like, conventional procedural programming languages, such as the "C" programming language, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, dynamic programming languages such as Python, Ruby and Groovy, or other programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for Example, through the Internet using an Internet Service Provider) or in a cloud computing environment or offered as a service such as a Software as a Service (SaaS).

[0052] Furthermore, the recited order of processing elements or sequences, or the use of numbers, letters, or other designations therefore, is not intended to limit the claimed processes and methods to any order except as may be specified in the claims. Although the above disclosure discusses through various examples what is currently considered to be a variety of useful embodiments of the disclosure, it is to be understood that such detail is solely for that purpose, and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover modifications and equivalent arrangements that are within the scope of the disclosed embodiments. For example, although the implementation of various components described above may be embodied in a hardware device, it may also be implemented as a software only solution, e.g., an installation on an existing server or mobile device.

[0053] Similarly, it should be appreciated that in the foregoing description of embodiments of the present disclosure, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the various embodiments. This method of disclosure, however, is not to be interpreted as reflecting an intention that the claimed subject matter requires more features than are expressly recited in each claim. Rather, claimed subject matter may lie in less than all features of a single foregoing disclosed embodiment.

[0054] In some embodiments, the numbers expressing quantities or properties used to describe and claim certain embodiments of the application are to be understood as being modified in some instances by the term "about," "approximate," or "substantially." Unless otherwise stated, "about," "approximate," or "substantially" may indicate ±20% variation of the value it describes. Accordingly, in some embodiments, the numerical parameters set forth in the written description and attached claims are approximations that may vary depending upon the desired properties sought to be obtained by a particular embodiment. In some embodiments, the numerical parameters may take a prescribed effective digit into account and adopt a general method to approximate the numerical parameters. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of some embodiments of the application are approximations, the numerical values set forth in the specific examples are reported as precisely as practicable.

[0055] For each of the patents, patent applications, patent application publications and other materials, such as articles, books, instructions, publications, documents, articles, etc., cited in this application are hereby incorporated by reference in their entirety. Application history documents that are inconsistent or conflicting with the contents of the present application are excluded, and documents (currently or later attached to the present application) that limit the widest range of the scope of the present application are also excluded. It should be noted that if the description, definition, and / or terms used in the appended application of the present disclosure is inconsistent or conflicting with the content described in the present disclosure, the use of the description, definition and / or terms of the Current disclosure shall prevail.

[0056] In closing, it is to be understood that the embodiments of the application disclosed herein are illustrative of the principles of the embodiments of the application. Other modifications may be employed may be within the scope of the claims.

Claims

1. A system (100) for tissue density analysis, comprising: an acquisition module (410) configured to obtain image data and tissue density distribution data of a target tissue, wherein the tissue density distribution data includes CT values based on the image data; a display module (420) configured to: display the image data; and display the tissue density distribution data in a plurality of charts including density segmentations, wherein the plurality of charts include a CT value bar chart (750), a histogram (760), and a table (770), the histogram (760) representing a volume distribution of regions having different CT values in the target tissue, and the table (770) representing volumes and volume percentages of the density segmentations; and a processing module (430) configured to: process, based on at least one of an annotation, a click, a double-click, or a voice input, the tissue density distribution data displayed in the plurality of charts by adjusting at least part of the density segmentations, including: adjusting a division of the density segmentations by adjusting one or more sliders in the CT value bar chart (750); and adjusting the density segmentations in the histogram (760) and / or the table (770) according to an adjustment result of the density segmentations of the CT value bar chart (750), wherein the volumes and the volume percentages in the table (770) are redetermined based on the adjusted density segmentations; and adjust the image data based on the adjustment result of the at least part of the density segmentations; wherein the display module (420) is further configured to display the adjusted image data and the processed tissue density distribution data.

2. The system of claim 1, wherein the processing module (430) is further configured to: adjust the at least part of the density segmentations through one or more tissue density segmentation thresholds.

3. The system of claim 2, wherein the processing module (430) is further configured to: modify a tissue density segmentation threshold, add a tissue density segmentation threshold, and / or delete a tissue density segmentation threshold with the at least one of the annotation, the click, the double-click, or the voice input.

4. The system of any one of claims 1 to 3, wherein the processing module (430) is further configured to: update the tissue density distribution data in the plurality of charts simultaneously according to the adjustment result.

5. The system of claim 4, wherein the processing module (430) is configured to: update at least one of a color or statistics data of a same density segmentation in the plurality of charts simultaneously according to the adjustment result.

6. A method for tissue density analysis, comprising: obtaining image data and tissue density distribution data of a target tissue, wherein the tissue density distribution data includes CT values based on the image data; displaying the image data; and displaying the tissue density distribution data in a plurality of charts including density segmentations, wherein the plurality of charts include a CT value bar chart (750), a histogram (760), and a table (770), the histogram (760) representing a volume distribution of regions having different CT values in the target tissue, and the table (770) representing volumes and volume percentages of the density segmentations; processing, based on at least one of an annotation, a click, a double-click, or a voice input, the tissue density distribution data displayed in the plurality of charts by adjusting at least part of the density segmentations, including: adjusting a division of the density segmentations by adjusting one or more sliders in the CT value bar chart (750); and adjusting the density segmentations in the histogram (760) and / or the table (770) according to an adjustment result of the density segmentations of the CT value bar chart (750), wherein the volumes and the volume percentages in the table (770) are redetermined based on the adjusted density segmentations; adjusting the image data based on the adjustment result of the at least part of the density segmentations; and displaying the adjusted image data and the processed tissue density distribution data.

7. The method of claim 6, wherein adjusting, based on at least one of an annotation, a click, a double-click, or a voice input, at least part of the density segmentations comprises: adjusting the at least part of the density segmentations through one or more tissue density segmentation thresholds.

8. The method of claim 7, wherein adjusting one or more tissue density segmentation thresholds comprises: modifying a tissue density segmentation threshold, adding a tissue density segmentation threshold, and / or deleting a tissue density segmentation threshold with the at least one of the annotation, the click, the double-click, or the voice input.

9. The method of any one of claims 6 to 8, further comprising: updating the tissue density distribution data in the plurality of charts simultaneously according to the adjustment result.

10. The method of claim 9, further comprising: updating at least one of a color or statistics data of a same density segmentation in the plurality of charts simultaneously according to the adjustment result.

11. A non-transitory computer readable medium storing a computer program, the computer program including instructions configured to: obtain image data and tissue density distribution data of a target tissue, wherein the tissue density distribution data includes CT values based on the image data; display the image data; display the tissue density distribution data in a plurality of charts including density segmentations, wherein the plurality of charts include a CT value bar chart (750), a histogram (760), and a table (770), the histogram (760) representing a volume distribution of regions having different CT values in the target tissue, and the table (770) representing volumes and volume percentages of the density segmentations; process, based on at least one of an annotation, a click, a double-click, or a voice input, the tissue density distribution data displayed in the plurality of charts by adjusting at least part of the density segmentations, including: adjusting a division of the density segmentations by adjusting one or more sliders in the CT value bar chart (750); and adjusting the density segmentations in the histogram (760) and / or the table (770) according to an adjustment result of the density segmentations of the CT value bar chart (750), wherein the volumes and the volume percentages in the table (770) are redetermined based on the adjusted density segmentations; adjust the image data based on the adjustment result of the at least part of the density segmentations; and display the adjusted image data and the processed tissue density distribution data.