Systems and methods for modifying images

Abstract

The method for modifying pixel luminance values ​​of a digital image includes identifying a measured luminance value for each of a plurality of pixels, determining a location of the plurality of pixels corresponding to the artificial object in the digital image based on the measured luminance value of each of the plurality of pixels, and adjusting the measured luminance value of each of the pixels at the plurality of pixel locations corresponding to the artificial object in the digital image to a predetermined luminance value. The method for modifying pixel tone values ​​of a digital image includes calculating a tone transform configured to suppress tones of the artificial object in the digital image, and applying the tone transform to each of the pixels at the plurality of pixel locations corresponding to the artificial object in the digital image.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. patent application Ser. No. 17 / 962,886, filed Oct. 10, 2022, the entire contents of which are incorporated herein by reference. [Technical Field]

[0002] The disclosed subject matter relates to systems and methods for modifying pixel brightness in images, such as medical images, and more particularly, in Digital Imaging and Communications in Medicine (DICOM) standard objects. The systems and methods described herein can adjust pixel brightness in digital images and suppress bright pixels using tone transformation logic. [Background technology]

[0003] In medical imaging, Picture Archiving and Communication Systems (PACS) are a combination of computers and networks dedicated to storing, retrieving, displaying, and distributing images. Medical information can be stored in a variety of formats, but a common format for image storage is DICOM. DICOM is a standard that, among other things, allows medical images and associated metadata to be communicated from imaging modalities (e.g., X-ray (or its digital counterparts: computed radiography ("CR") and digital radiography ("DR")), computed tomography ("CT"), and magnetic resonance imaging ("MRI") devices) to remote storage and / or client devices for viewing and / or other uses.

[0004] When viewing medical images stored in DICOM format, it can be important for users to accurately read and identify individual pixel values ​​to properly interpret the image. However, the human eye can be significantly affected by the brightness of background pixels. Furthermore, large contrasts between bright and dark pixels can strain the user's eyes. Therefore, it can be beneficial to adjust the brightness values ​​of individual pixels in medical images.

[0005] Typically, a large contrast between bright and dark images occurs when a medical image contains an artificial object, such as a breast implant. The implant can be significantly brighter than the surrounding tissue, and the radiologist reviewing the medical image may be affected by the brightness of the implant when attempting to view the surrounding tissue.

[0006] Therefore, there is a need for a system and method for modifying the brightness of pixels in an image. Summary of the Invention

[0007] The objects and advantages of the disclosed subject matter will be set forth in and become apparent from the following description, as well as be realized by the practice of the disclosed subject matter. Additional advantages of the disclosed subject matter will be realized and attained by the methods and systems particularly pointed out in the specification and claims thereof, as well as the appended drawings.

[0008] To achieve these and other advantages, and in accordance with the objectives of the disclosed subject matter, as embodied and broadly described, the disclosed subject matter relates to a system and method for modifying luminance values ​​of pixels in an image. For example, a method for modifying pixel luminance values ​​of a digital image, the method including: receiving, at one or more computing devices, a digital image having a plurality of pixels; determining, at the one or more computing devices, measured luminance values ​​of each of the plurality of pixels; determining, at the one or more computing devices, locations of the plurality of pixels that correspond to an artificial object in the digital image based on the measured luminance values ​​of each of the plurality of pixels; and adjusting, at the one or more computing devices, the measured luminance values ​​of each of the pixels at the locations of the plurality of pixels that correspond to the artificial object in the digital image to a predetermined luminance value to form a new digital image.

[0009] The predetermined luminance value may be less than the measured luminance value. In the one or more computing devices, determining a location of the plurality of pixels corresponding to the artificial object in the digital image based on the luminance value of each of the plurality of pixels may include assigning to each of the plurality of pixels either a first value if the measured luminance value of each of the plurality of pixels is greater than a threshold value, or a second value if the measured luminance value of each of the plurality of pixels is less than a threshold value. The threshold value may be any value between 75% and 95% of a maximum luminance value of the digital image.

[0010] The locations of the plurality of pixels corresponding to the artificial object in the digital image can be based on whether the plurality of pixels are assigned the first value. The method can further include displaying the new digital image on one or more computing devices.

[0011] In accordance with the disclosed subject matter, there is provided a system including one or more processors and a memory coupled to the processor containing instructions executable by the processor that, when executed, are operable to receive a digital image having a plurality of pixels, identify a measured luminance value for each of the plurality of pixels, determine a location of the plurality of pixels corresponding to an artificial object in the digital image based on the measured luminance value of each of the plurality of pixels, and adjust the measured luminance value of each of the pixels at the location of the plurality of pixels corresponding to the artificial object in the digital image to a predetermined luminance value to form a new digital image.

[0012] In accordance with the disclosed subject matter, a method is provided for modifying pixel tone values ​​of a digital image, the method including: receiving, at one or more computing devices, a digital image having a plurality of pixels; identifying, at the one or more computing devices, measured luminance values ​​for each of the plurality of pixels; determining, at the one or more computing devices, locations of the plurality of pixels corresponding to an artificial object in the digital image based on the measured luminance values ​​for each of the plurality of pixels; and calculating, at the one or more computing devices, a tone transformation configured to suppress tones of the artificial object in the digital image. The tone transformation includes measuring, at the one or more computing devices, a pixel tone value of at least one of the digital images; analyzing, at the one or more computing devices, the at least one pixel tone value of the digital image to calculate a target pixel tone value based on the locations of the plurality of pixels corresponding to the artificial object in the digital image; and adjusting, at the yet another computing device, the at least one pixel tone value of the digital image to the target pixel tone value. The method also includes applying, at the one or more computing devices, the tone transformation to each of the pixels at the locations of the plurality of pixels corresponding to the artificial object in the digital image to form a new digital image.

[0013] The at least one pixel tone value may be at least one of a maximum pixel tone value, a minimum pixel tone value, and an image histogram. If the at least one pixel tone value is the image histogram, the tone conversion may include determining an artificial object histogram based on the locations of the plurality of pixels corresponding to the artificial object in the digital image. The artificial object histogram may have a first window width, the image histogram may have a second window width, the first window width may have a first window center, and the second window width may have a second window center. Calculating the target pixel tone value includes at least one of adjusting the first window width to be approximately equal to the second window width and adjusting the first window center to be approximately equal to the second window center.

[0014] In accordance with the disclosed subject matter, a system is provided that includes one or more processors and a memory coupled to the processor that includes instructions executable by the processor. The processor, when executing the instructions, is operable to receive a digital image having a plurality of pixels, identify a measured luminance value for each of the plurality of pixels, determine locations of the plurality of pixels corresponding to an artificial object in the digital image based on the measured luminance value for each of the plurality of pixels, and calculate a tone transformation configured to suppress tones of the artificial object in the digital image. The tone transformation can include instructions for measuring an image histogram of the digital image, analyzing the image histogram to determine an artificial object image histogram based on the locations of the plurality of pixels corresponding to the artificial object in the digital image, and adjusting the artificial object image histogram to form a target image histogram. The processor, when executing the instructions, is also operable to apply the tone transformation to the locations of the plurality of pixels corresponding to the artificial object in the digital image to form a new digital image. [Brief explanation of the drawings]

[0015] [Figure 1] 1 illustrates a hierarchy of medical image records that may be modified in accordance with the disclosed subject matter. [Figure 2] 1 illustrates the architecture of a system for modifying the intensity of pixels of a digital image by masking in accordance with the disclosed subject matter. [Figure 3] 1 illustrates a medical image including an artificial object in accordance with the disclosed subject matter. [Figure 4A] 4 shows a binarized digital image of the medical image of FIG. 3. [Figure 4B] 4B shows an extracted image in which the largest objects are extracted from the binarized digital image of FIG. 4A. [Figure 4C] 4C shows a modified image of the extracted image of FIG. 4B in accordance with the disclosed subject matter. [Figure 5] 4 shows a modified medical image of the medical image of FIG. 3. [Figure 6] 1 shows a medical image modified by tone suppression in accordance with the disclosed subject matter. [Figure 7A] 10 shows an image histogram before tone suppression in accordance with the disclosed subject matter. [Figure 7B] 10 shows an image histogram after tone suppression in accordance with the disclosed subject matter. [Figure 8] 10 shows an extracted image identifying a boundary region in accordance with the disclosed subject matter. [Figure 9] 1 shows a medical image with a modified boundary in accordance with the disclosed subject matter. [Figure 10A] 1 illustrates a binarized image including an artificial object in accordance with the disclosed subject matter. [Figure 10B] 1 illustrates a binarized image including an artificial object in accordance with the disclosed subject matter. [Figure 10C] 1 illustrates a binarized image including an artificial object in accordance with the disclosed subject matter. [Figure 11] 10A-10C show a binarized image including an artificial object that combines the artificial objects of FIGS. 10A-10C in accordance with the disclosed subject matter. [Figure 12] 1 is a flowchart illustrating a method for modifying the intensity of pixels in a digital image by masking in accordance with the disclosed subject matter. [Figure 13] 1 is a flowchart illustrating a method for modifying the luminance of pixels of a digital image by tone transformation in accordance with the disclosed subject matter. [Figure 14] 1 is a flowchart illustrating how tone transformation suppresses tone of artificial objects in a digital image in accordance with the disclosed subject matter. DETAILED DESCRIPTION OF THE INVENTION

[0016] Reference will now be made in detail to various exemplary embodiments of the disclosed subject matter, which are illustrated in the accompanying drawings. For purposes of explanation and not limitation, systems and methods are described herein for modifying the intensity of pixels in digital images, particularly digital medical images (also referred to as "medical images"), and more particularly DICOM images. However, the methods and systems described herein may be used to modify the intensity of pixels in any digital image. As used in this specification and the appended claims, the singular forms "a," "an," and "the," etc., are intended to include the plural forms unless the context clearly dictates otherwise. Thus, as used herein, the term medical image may refer to a single medical image or to multiple medical images. For example, and referring to FIG. 1 for purposes of explanation and not limitation, a medical image record as referred to herein may include a single DICOM Service-Object Pair (SOP) Instance (also referred to as a "DICOM Instance," "DICOM Image," and "Image") 1 (e.g., 1A-1H), one or more DICOM SOP Instances 1 in one or more Series 2 (e.g., 2A-D), one or more Series 2 in one or more Analyses 3 (e.g., 3A, 3B), and one or more Analyses 3. A DICOM image may have a photometric interpretation tag associated with it. A photometric interpretation tag may identify, for example, that the image may be interpreted as Monochrome 1, Monochrome 2, RGB, YBR_Full, etc. A DICOM image may have a window center attribute. A DICOM image may have a window width attribute.

[0017] For purposes of explanation and not limitation, and referring to FIGS. 2-5 , the disclosed system 100 may be configured to modify pixel brightness values ​​of a digital image. For example, the system 100 may be configured to modify pixel brightness values ​​of a medical image record, such as a DICOM image (e.g., 1J). Specifically, the system 100 may modify brightness values ​​of a DICOM image 1 (e.g., 1J) to make the DICOM image 1 (e.g., 1J) easier to read, for example, to perform a medical diagnosis. The system 100 may include one or more computing devices defining a server 30 and a user workstation 60. The user workstation 60 may be connected to the server 30 by a network. The network may be, for example, a local area network (LAN), a wireless LAN (WLAN), a virtual private network (VPN), or any other network allowing radio frequency or wireless-type connectivity. For example, other radio frequencies or wireless connections may include one or more network access technologies such as, but not limited to, Global System for Mobile communications (GSM), Universal Mobile Telecommunications System (UMTS), General Packet Radio Services (GPRS), Enhanced Data GSM Environment (EDGE), Third Generation Partnership Project (3GPP) technologies (including Long Term Evolution (LTE), LTE-Advanced, 3G technologies, Internet of Things (IoT), fifth generation (5G)), or new radio (NR) technologies. Other examples may include Wideband Code Division Multiple Access (WCDMA), Bluetooth, IEEE 802.11b / g / n, or any other 802.11 protocol, or any other wired or wireless connection.

[0018] The workstation 60 can take the form of any known client device. For example, the workstation 60 can be a computer, such as a laptop or desktop computer, a personal data assistant / personal digital assistant (PDA), or any other user equipment or tablet, such as a mobile device or mobile portable media player. The server 30 can be a service point that provides processing, database, and communication capabilities. For example, the server 30 can include a dedicated rack-mounted server, a desktop computer, a laptop computer, a set-top box, an integrated device that combines various functions, such as the functions of two or more of the foregoing devices, etc. The server 30 can vary in configuration and functionality, but can include one or more processors, memory, and / or transceivers. The server 30 can also include one or more mass storage devices, one or more power sources, one or more wired or wireless network interfaces, one or more input / output interfaces, and / or one or more operating systems.

[0019] A user may be anyone authorized to access workstation 60 and / or server 30, including a medical professional, medical technician, researcher, or patient. In some embodiments, a user authorized to use workstation 60 and / or communicate with server 30 may have a username and / or password that can be used to log in to or access workstation 60 and / or server 30.

[0020] The workstation 60 may include a GUI 65, a memory 61, a processor 62, and a transceiver 63. Medical image records 10 received by the workstation 60 may be processed using one or more processors 62. The processor 62 may be any hardware or software used to execute computer program instructions. These computer program instructions may be provided to a processor in a general-purpose computer to modify its functionality into a specific application, a special-purpose computer, an application-specific integrated circuit (ASIC), or other programmable digital data processing device, and the instructions executed via the processor of the workstation 60 or other programmable data processing device cause it to perform the functions / operations specified in the block diagram or operational block(s), thereby modifying its functionality in accordance with embodiments herein. The processor 62 may be a portable, embedded microcontroller or microcomputer. For example, the processor 62 may be embodied by any computing or data processing device, such as a central processing unit (CPU), a digital signal processor (DSP), an ASIC, a programmable logic device (PLD), a field programmable gate array (FPGA), a digital expansion circuit, or equivalent devices, or a combination thereof. Processor 62 may be implemented as a single controller or as multiple controllers or processors.

[0021] The workstation 60 can send and receive medical image records 10 from the server 30 using a transceiver 63. The transceiver 63 can be a unit or device independently configurable as a transmitter, a receiver, or both a transmitter and a receiver, or both a transmitter and a receiver. In other words, the transceiver 63 can include any hardware or software that enables the workstation 60 to communicate with the server 30. The transceiver 63 can be a wired transceiver or a wireless transceiver. If wireless, the transceiver 63 can be implemented as a remote radio head located on a mast (antenna) rather than as a device itself. Although FIG. 2 illustrates only a single transceiver 63, the workstation 60 can include one or more transceivers 63. The memory 61 can be a non-volatile storage medium or any other suitable storage device, such as a non-transitory computer-readable medium or storage medium. For example, memory 61 may be random access memory (RAM), read-only memory (ROM), hard disk drive (HDD), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash memory, or other solid-state memory technology. Memory 61 may also be a compact disc read-only optical memory (CD-ROM), digital versatile disc (DVD), any other optical storage, magnetic cassette, magnetic tape, magnetic disk storage, or other magnetic storage device, or any other physical or material medium that can be used to tangibly store desired information, data, or instructions and that can be accessed by a computer or processor. Memory 61 may be removable or non-removable.

[0022] As shown in Figure 3, for purposes of explanation and not limitation, the medical image record 10 can be a DICOM image (e.g., 1J). Figure 3 shows only one DICOM image 1J for clarity. The DICOM image can be, for example, a digital mammography x-ray image or other two-dimensional medical image. The DICOM can also be, for example, a breast tomosynthesis image or other three-dimensional medical image.

[0023] In operation, and for purposes of explanation and not limitation, and described with reference to Figures 2-5, the system 100 can be used to modify pixel intensity values ​​of a medical image record 10. The medical image record 10 can be received by a workstation 60, and instructions can be provided to the workstation 60 to modify pixel intensity values ​​of the medical image record 10, and in particular, each DICOM image 1 (e.g., 1J). The instructions can originate from a server processor 31 on the server 30. The instructions can be provided by a local processor of the workstation 60, or by both the server processor 31 of the server 30 and a local processor of the workstation 60. The process is described below with reference to a DICOM image 1J, but can also be performed for multiple DICOM images 1 (e.g., 1J). Alternatively, or additionally, the process can be performed for one or more digital images in any suitable format.

[0024] The workstation 60 can determine pixel intensity values ​​for multiple pixels in the DICOM image 1J through measuring the intensity of each pixel in the multiple pixels in the DICOM image 1J. The DICOM image 1J can have a maximum pixel intensity value. Each pixel in the multiple pixels in the DICOM image 1J has an initial intensity value. The initial intensity value can be represented as an 8-bit grayscale value, such as an 8-bit Monochrome1 value or an 8-bit Monochrome2 value. The measurement of pixel intensity values ​​can be performed using various techniques known in the art. For example, the DICOM image can have pixel values ​​for each of the multiple pixels in the image, a window center and a window width for the pixel values ​​of the DICOM image. From the window center and window width, the slope and intercept can be calculated using the following formula: (1) Slope = (maximum pixel brightness value) / (window width) (2) Intercept = -slope * window center + (maximum pixel brightness value) / 2 where the maximum pixel brightness value can be, for example, 255. Using the slope, intercept, and pixel value, an 8-bit grayscale value can be determined using the following formula: (3) 8-bit grayscale value = pixel value * slope + intercept If the photometric interpretation tag of a DICOM image is, for example, Monochrome1, then the 8-bit grayscale value is assigned as an 8-bit Monochrome1 value. The 8-bit Monochrome2 value is calculated using the following formula: (4) 8-bit monochrome2 value = maximum pixel brightness value - 8-bit monochrome1 value An 8-bit Monochrome2 value can be assigned as the initial luminance value.

[0025] The workstation 60 can determine the location of a plurality of pixels in the DICOM image 1J that correspond to an artificial object region 401 located within the patient's body. The artificial object region 401 in the DICOM image 1J can be located using various techniques. For example, the artificial object region 402 can be located using binarization and extraction techniques, as shown in Figures 4A and 4B, respectively.

[0026] As shown in FIG. 4A , the binarization technique may involve capturing a DICOM image 1J and changing the pixel brightness values ​​of a plurality of pixels in the DICOM image 1J to either a first brightness value or a second brightness value. For example, the plurality of pixels in the DICOM image 1J may be changed to either bright, i.e., a first brightness value, or dark, i.e., a second brightness value. The first brightness value may be a value of 1. The second brightness value may be a value of 0. Each pixel of the plurality of pixels in the DICOM image 1J may be determined to be bright or dark based on its measured brightness value. The binarization technique may include setting a threshold brightness value, or a binarization reference value. For each pixel of the plurality of pixels, if the measured brightness value of the pixel is greater than the binarization reference value, the binarization technique may change the pixel to a first brightness value. For each pixel of the plurality of pixels, if the measured brightness value of the pixel is less than the binarization reference value, the binarization technique may change the pixel to a second brightness value. For example, a binarization technique can be applied to all pixels of a DICOM image 1J to create a binarized image 1JA in which each pixel of the DICOM image 1J is either a bright pixel or a dark pixel, as shown in FIG. 4A. The binarization reference value can be set to 95% of the maximum pixel brightness value. Other suitable binarization reference values ​​can also be used, such as, but not limited to, 90%, 85%, or 80% of the maximum pixel brightness value. The binarization reference value can be 75% to 95% of the maximum brightness value.

[0027] As shown in FIG. 4B, the extraction technique can include taking a binarized image 1JA, such as that shown in FIG. 4A, and labeling the binarized image 1JA to identify a maximum object region 402. Labeling the binarized image 1JA can be performed according to methods known in the art for labeling pixels of an image. For example, the binarized image 1JA can be labeled using a process known as connected-component labeling to create a labeled image in which each pixel of the image is labeled. Using the labeled image, the maximum object region 402 can be identified by checking the total number of pixels for each label in the labeled image for the label with the largest number of pixels and assigning that label as the maximum object region 402. The maximum object region 402 has a plurality of pixels that can be labeled as the plurality of pixels corresponding to the maximum object region 402. The extraction technique can include retaining the locations of the plurality of pixels corresponding to the maximum object region 402. The extraction technique may also include extracting the largest object region 402 from the binarized image 1JA into a new extracted image 1JB, as shown in Figure 4B. The extracted image 1JB may include a plurality of pixels corresponding to the largest object region 402. The extracted image 1JB may include the locations of the plurality of pixels corresponding to the largest object region 402. The plurality of pixels corresponding to the largest object region 402 may have either a first luminance value or a second luminance value.

[0028] As shown in Figure 4C, the extraction technique takes extracted image 1JB and sets the pixel intensity value of each of the pixels corresponding to maximum object region 402 to a first intensity value representing a bright pixel to create modified extracted image 1JC, where all of the pixels in maximum object region 402 have the first intensity value and each of the pixels in maximum object region 402 can be labeled as pixels corresponding to artificial object region 401 in DICOM image 1J. The locations of the pixels corresponding to maximum object region 402 can be assigned as the locations of the pixels corresponding to artificial object region 401 in DICOM image 1J. Thus, as shown in Figure 4C, each of the pixels corresponding to artificial object region 401 can have the first intensity value.

[0029] As shown in FIG. 5 , the workstation 60 can adjust pixel luminance values ​​of the artificial object region 401 of the DICOM image 1J to a predetermined luminance value to generate a modified DICOM image 1JD. The workstation 60 can modify pixel luminance values ​​at the location of the artificial object region 401 of the DICOM image 1J to create a modified artificial object region 403 in the DICOM image 1J. The predetermined luminance value can be assigned as a gray pixel having a pixel luminance value of 128. The predetermined luminance value can be assigned as a dark pixel having a pixel luminance value of 0. The modified artificial object region 403 can have a pixel luminance value that is less than the brightest measured pixel value in the artificial object region. For example, the modified artificial object region 403 can have a pixel luminance value set to a predetermined luminance value. For example, as shown in FIG. 5 , the modified artificial object region 403 can have pixel luminance values ​​that are reduced in luminance. In accordance with the disclosed subject matter, the modified artificial object region 403 can have a pixel luminance value of 0. Therefore, the modified artificial object region 403 can be masked to create a modified DICOM image 1JD, as shown in FIG.

[0030] The workstation 60 can modify pixel tone values ​​of the DICOM image 1J to create a tone-suppressed DICOM image 1JE, as shown in FIG. 6 . The tone-suppressed DICOM image 6J can have its pixel tone values ​​modified using various techniques. For example, tone suppression techniques, or tone conversion, can be used, as shown in FIG. 6 . The tone conversion can include measuring at least one pixel tone value of the DICOM image 1J. In accordance with the disclosed subject matter, the at least one pixel tone value can include an image histogram 11 of the DICOM image 1J, as shown in FIG. 7A . The image histogram 11 has an image histogram center, or image window center, and an image dynamic range, or image window width, as known to those skilled in the art. The at least one pixel tone value can also include a maximum pixel value and / or a minimum pixel value of the DICOM image 1J.

[0031] The tone transformation can include calculating a target pixel tone value based on at least one pixel tone value and a plurality of pixel locations. According to the disclosed subject matter, the at least one pixel tone value can include an artificial object histogram 12 by calculating an artificial object histogram for a plurality of pixel locations corresponding to the artificial object region 401, as shown in FIG. 4C . The artificial object histogram 12 has an object histogram center, i.e., an object window center, and an object dynamic range, or object window width. The tone transformation can shift or adjust at least one pixel tone value to the target pixel tone value. According to the disclosed subject matter, the artificial object histogram 12 or at least one pixel tone value is adjusted to the window center of the image histogram 11, as shown in FIG. 7B , to create a tone-transformed image histogram 13, or a target pixel tone value. The tone-transformed image histogram 13 can have a transformed histogram center, or a transformed window center, and a transformed dynamic range, or a transformed window width. The tone transformation can then apply the tone transformed image histogram 12 to the plurality of pixels corresponding to the modified artificial object region 404, as shown in Figure 6. At least one pixel tone value, which may include a maximum pixel value and / or a minimum pixel value, can be used to calculate a target pixel tone value from which the plurality of pixel tone values ​​of the DICOM image 1J can be adjusted to the target pixel tone value.

[0032] The tone transformation can be calculated according to the following formula: (5) Slope = (image window width) / (object window width)*suppression rate (6) Intercept = -slope * object window center + image window center (7) Suppressed object pixel value = slope * object pixel value + intercept The suppression ratio in the above equation is a system-defined ratio that affects the strength of tone suppression. The suppression ratio can be automatically determined based on the image. The suppression ratio can be determined by a user of the system. The object pixel values ​​can be pixel tone values ​​of a plurality of pixels corresponding to the artificial object 401. The suppressed object pixel values ​​can be pixel tone values ​​of the transformed artificial object region 404. As mentioned above, the suppressed object pixel values ​​can also correspond to target pixel values. Therefore, the pixel tone values ​​of the transformed artificial object region 404 can be changed to create a tone-transformed DICOM image 1JE, as shown in FIG. 6.

[0033] The workstation 60 can detect and modify the boundary region 410 of the transformed artificial object region 404 in the tone-converted DICOM image 1JF, as shown in FIG. 8 . The detection and modification of the boundary region 410 can also be performed in the modified DICOM image 1JD. The boundary region 410 can be located by scanning all pixels in the DICOM image 1JF from left to right to find the first bright pixel and assigning that pixel as a boundary pixel. The workstation 60 then continues scanning back to the left side of the image, scanning the next row of pixels until it finds a second bright pixel and assigns that pixel as a boundary pixel. This process continues throughout the entire image 1JD until each row of pixels has been scanned. The scanning can be performed in any suitable organized process (e.g., from right to left or bottom to top). The workstation 60 then assigns the pixels assigned as boundary pixels as the boundary region 410. Using the boundary region 410, the workstation 60 can change the pixel intensity values ​​of the boundary region 410 in the tone-converted DICOM image 1JE to a predetermined intensity value, thereby creating a boundary-modified DICOM image 1JG as shown in FIG. 9.

[0034] The workstation 60 can modify pixel brightness values ​​or modify pixel grayscale values ​​of a three-dimensional DICOM image using the techniques described above. Modifying pixel brightness values ​​or pixel grayscale values ​​of an artificial object in a three-dimensional DICOM image, such as a breast tomosynthesis image, can be performed by calculating a three-dimensional artificial object region and modifying the brightness values ​​or pixel grayscale values ​​of the three-dimensional artificial object region to create a modified three-dimensional DICOM image. The three-dimensional artificial object region can be calculated in various ways. The three-dimensional artificial object region can be calculated by locating a target artificial object region in the three-dimensional DICOM image, such as the center of the three-dimensional DICOM image, and applying the target artificial object region to the three-dimensional DICOM image.

[0035] It is also possible to calculate a 3D artificial object region using a 2D composite image of a 3D DICOM image to create a 2D composite artificial object region. The 2D composite artificial object region is calculated in the same way as the artificial object region of the modified DICOM image 1JD. The same technique can be used to modify pixel intensity values ​​of a 3D DICOM image to form a modified 3D DICOM image.

[0036] Additionally, a three-dimensional artificial object region can be calculated using multiple frames of the three-dimensional DICOM image. Multiple artificial object regions can be calculated using the techniques described above using multiple frames of the three-dimensional DICOM image. The multiple artificial object regions can then be combined to select a single combined artificial object region that can be applied to the three-dimensional DICOM image. The combined artificial object region can be the largest of the multiple artificial object regions calculated using the techniques described above. A three-dimensional DICOM image can include multiple frames. Using the binarization and extraction processes described above for two-dimensional DICOM images, the multiple frames of the three-dimensional DICOM image can be binarized and extracted to form multiple masking frames. The multiple masking frames can then be combined to form a combined masking image having combined artificial object regions. As shown in FIGS. 10-11 (three frames are shown for simplicity, but any number of frames can be used), a first masking frame 1JH in FIG. 10A, a second masking frame 1JI in FIG. 10B, a third masking frame 1JJ in FIG. 10C, and a combined masking image 1JK in FIG. 11 are formed. Each of the masking frames 1JH, 1JI, and 1JJ has an artificial object region 401. The masking frame 1JK in FIG. 11 includes a combined artificial object region 405. The combined masking image 1JK can be calculated by obtaining binarized pixel values ​​of each of the multiple masking frames and comparing them with corresponding pixels of the other multiple masking frames. The binarized pixel values ​​can be combined using the following formula to form a combined pixel value: (8) Combined pixels = Frame 1 pixels | Frame 2 pixels | ... | Frame n pixel The combined pixels can be used to form a combined masking frame 1JK and a combined artificial object region 405. The combined artificial object region 405 can then be applied to each frame of the 3D DICOM image to mask out the 3D artificial object region using the process described above with respect to Figures 4 and 5.

[0037] One or more of the DICOM images 1 (e.g., 1J, 1JA-1JG) may be displayed, for example, on a GUI 65. Providing an adjusted image can be important for a user to accurately read and identify individual pixel values ​​to properly interpret the image. The human eye can be significantly affected by the luminance of background pixels, and reducing the relative luminance of a particular pixel may make it less conducive to properly interpreting the image. Additionally, a large contrast between bright and dark pixels can strain the user's eyes. Therefore, adjusting the luminance values ​​of individual pixels in a medical image can be beneficial.

[0038] FIG. 12 illustrates an exemplary method 1000 for modifying pixel luminance values ​​of a digital image. The method may begin at step 1010, where the method includes receiving, at one or more computing devices, a digital image, the digital image having a plurality of pixels. At step 1020, the method may include determining, at the one or more computing devices, measured luminance values ​​for each of the plurality of pixels. At step 1030, the method may include determining, at the one or more computing devices, locations of the plurality of pixels corresponding to the artificial object in the digital image based on the measured luminance values ​​of each of the plurality of pixels. At step 1040, the method may include adjusting, at the one or more computing devices, the measured luminance values ​​of each of the pixels at the locations of the plurality of pixels corresponding to the artificial object in the digital image to a predetermined luminance value to form a new digital image. In accordance with the disclosed subject matter, the method may repeat one or more steps of the method of FIG. 12, as appropriate. Although the present disclosure describes and illustrates certain steps of the method of FIG. 12 as occurring in a particular order, the present disclosure contemplates any suitable steps of the method of FIG. 10 occurring in any suitable order. Additionally, although this disclosure describes and illustrates exemplary methods for modifying pixel luminance values ​​of a digital image that include particular steps of the method of Figure 12, this disclosure contemplates any suitable method for modifying pixel luminance values ​​of a digital image that includes any suitable steps, which may include all, some, or none of the steps of the method of Figure 12, where appropriate. Additionally, although this disclosure describes and illustrates particular components, devices, or systems that perform particular steps of the method of Figure 12, this disclosure contemplates any suitable combination of any suitable components, devices, or systems that perform any suitable steps of the method of Figure 12.

[0039] FIG. 13 illustrates an exemplary method 2000 for modifying pixel tone values ​​of a digital image. The method may begin at step 2010, where the method includes receiving, at one or more computing devices, a digital image, the digital image having a plurality of pixels. At step 2020, the method may include identifying, at one or more computing devices, measured luminance values ​​for each of the plurality of pixels. At step 2030, the method may include determining, at one or more computing devices, locations of the plurality of pixels corresponding to the artificial object in the digital image based on the measured luminance values ​​for each of the plurality of pixels. At step 2040, the method may include computing, at one or more computing devices, a tone transform configured to suppress tones of the artificial object in the digital image. As shown in FIG. 14, step 2040 may include step 2041, where one or more computing devices measure an image histogram of the digital image. As shown in FIG. 14, step 2040 may include step 2042, where one or more computing devices analyze the image histogram to determine an artificial object image histogram based on locations of the plurality of pixels corresponding to the artificial object in the digital image. As shown in Figure 14, step 2040 may include step 2043 of adjusting, at yet another computing device, the artificial object image histogram to form a target image histogram. Referring to Figure 13, at step 2050, the method may include applying, at one or more computing devices, a tone transform to each of pixels at a plurality of pixel locations corresponding to the artificial object in the digital image to form a new digital image. In accordance with the disclosed subject matter, the method may repeat one or more steps of the method of Figure 13, as appropriate. Although this disclosure describes and illustrates certain steps of the method of Figure 13 as occurring in a particular order, this disclosure contemplates any suitable steps of the method of Figure 13 occurring in any suitable order.Additionally, although this disclosure describes and illustrates exemplary methods for modifying pixel tone values ​​of a digital image that include particular steps of the method of Figure 13, this disclosure contemplates any suitable method for modifying pixel tone values ​​of a digital image that includes any suitable steps, which may include all, some, or none of the steps of the method of Figure 13, where appropriate. Additionally, although this disclosure describes and illustrates particular components, devices, or systems that perform particular steps of the method of Figure 13, this disclosure contemplates any suitable combination of any suitable components, devices, or systems that perform any suitable steps of the method of Figure 13.

[0040] The subject matter and operations described herein can be implemented in digital electronic circuitry, or in computer software, firmware, or hardware (including the structures disclosed herein and their structural equivalents), or in combinations of one or more of them. Embodiments of the subject matter described herein can also be implemented as one or more computer programs, i.e., one or more modules of computer program instructions, encoded on a computer storage medium for execution by, or to control the operation of, a data processing apparatus.

[0041] A computer storage medium may be or be included in a computer-readable storage device, a computer-readable storage substrate, a random-access or serial-access memory array or device, or a combination of one or more of these. Further, a computer storage medium is not a propagating signal, but a computer storage medium can be a source or destination of computer program instructions encoded in an artificially-generated propagating signal. A computer storage medium may also be or be included in one or more separate physical components or media (e.g., multiple CDs, disks, or other storage devices).

[0042] The term "processor" encompasses all types of apparatus, devices, and machines for processing data, including, by way of example, a programmable processor, a computer, a system-on-chip (single or multiple chips), or a combination thereof. An apparatus may include special-purpose logic circuitry such as an FPGA or an ASIC. In addition to hardware, an apparatus may also include code that establishes an execution environment for the computer program (e.g., code that constitutes processor firmware, a protocol stack, a database management system, an operating system, a cross-platform execution environment, a virtual machine, or one or more combinations thereof). The apparatus and execution environment may implement a variety of different computing model infrastructures, such as web services, distributed computing, or grid computing infrastructures.

[0043] A computer program (also known as a program, software, software application, script, or code) may be written in any type of programming language, including compiled or interpreted, declarative or procedural, and may be deployed in any form, such as a stand-alone program or as modules, components, subroutines, objects, or other units suitable for use in a computing environment. A computer program may, but need not, correspond to a file in a file system. A program may be stored as part of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program, or in multiple cooperating files (e.g., a file containing one or more modules, subprograms, or portions of code). A computer program may be deployed to run on one computer, on multiple computers at a single site, or on multiple computers distributed across multiple sites and interconnected by a communications network.

[0044] The processes and logic flows described herein may be performed by one or more programmable processors executing one or more computer programs, which perform actions by operating on input data and generating output. The processes and logic flows may also be performed by, or devices may be implemented as, special purpose logic circuitry (e.g., FPGAs or ASICs).

[0045] Processors suitable for the execution of a computer program can include, by way of example and not limitation, both general-purpose and special-purpose microprocessors. Devices suitable for storing computer program instructions and data can include all forms of non-volatile memory, media, and memory devices, including, by way of example and not limitation, semiconductor memory devices (e.g., EPROM, EEPROM, and flash memory devices), magnetic disks (e.g., internal or removable disks), magneto-optical disks, and CD-ROM and DVD-ROM disks. The processor and memory can be supplemented by, or incorporated in, special-purpose logic circuitry.

[0046] Additionally, as described above in connection with particular embodiments, certain components may communicate with other certain components, for example, via a network (e.g., a local area network or the Internet). Unless expressly stated above, the disclosed subject matter is intended to encompass each transaction, including both sending and receiving. Those skilled in the art will readily understand that with respect to the features described above, if one component sends, transmits, or otherwise makes available to another component, the other component will receive or acquire it, whether or not expressly stated.

[0047] In addition to the specific embodiments claimed below, the disclosed subject matter also relates to other embodiments having the dependent features claimed below and any other possible combinations of the above-disclosed features. As such, the specific features recited in the dependent claims and disclosed above can be combined with each other in other possible combinations. Accordingly, the foregoing description of specific embodiments of the disclosed subject matter has been presented for purposes of illustration and description and is not intended to be exhaustive or to limit the disclosed subject matter to the disclosed embodiments.

[0048] It will be apparent to those skilled in the art that various modifications and variations can be made in the method and system of the disclosed subject matter without departing from the spirit or scope of the disclosed subject matter. Thus, it is intended that the disclosed subject matter cover modifications and variations that come within the scope of the appended claims and their equivalents.

Claims

1. 1. A method for modifying pixel luminance values ​​of a digital image, comprising: receiving, at one or more computing devices, a digital image having a plurality of pixels; determining, at the one or more computing devices, a measured luminance value for each of the plurality of pixels; determining, at the one or more computing devices, locations of the plurality of pixels corresponding to the artificial object in the digital image based on the measured luminance values ​​of each of the plurality of pixels; adjusting, at the one or more computing devices, the measured luminance values ​​of each of the pixels at the plurality of pixel locations corresponding to the artificial object in the digital image to a predetermined luminance value to form a new digital image. A method comprising:

2. The method of claim 1 , wherein the predetermined luminance value is less than the measured luminance value.

3. In the one or more computing devices, determining a location of the plurality of pixels corresponding to the artificial object in the digital image based on the luminance value of each of the plurality of pixels includes: a first value if the measured luminance value of each of the plurality of pixels is greater than a threshold; and a second value if the measured luminance value of each of the plurality of pixels is less than a threshold value; The method of claim 1 , comprising assigning either:

4. The method of claim 3 , wherein the threshold is determined by an input.

5. The method of claim 3 , wherein the locations of the plurality of pixels corresponding to the man-made object in the digital image are based on whether the plurality of pixels are assigned the first value.

6. The method of claim 1 , further comprising displaying the new digital image on one or more computing devices.

7. 1. A system including one or more processors and a memory coupled to the processors containing instructions executable by the processors, the instructions, when executed by the processor, receiving a digital image having a plurality of pixels; identifying a measured luminance value for each of the plurality of pixels; determining a location of the plurality of pixels corresponding to an artificial object in the digital image based on the measured luminance value of each of the plurality of pixels; adjusting the measured luminance values ​​of each of the pixels at the plurality of pixel locations corresponding to the artificial object in the digital image to a predetermined luminance value to form a new digital image. A system capable of operating as follows.

8. The system of claim 7 , wherein the predetermined luminance value is less than the measured luminance value.

9. The instructions for determining the location of the plurality of pixels corresponding to the artificial object in the digital image based on the luminance value of each of the plurality of pixels include, for each of the plurality of pixels: a first value if the measured luminance value of each of the plurality of pixels is greater than a threshold; and a second value if the measured luminance value of each of the plurality of pixels is less than a threshold value; The system of claim 7, further comprising: assigning one of the following:

10. The system of claim 9 , wherein the threshold is between 75% and 95% of the maximum luminance value of the digital image.

11. The system of claim 9 , wherein the locations of the plurality of pixels corresponding to the man-made object in the digital image are based on whether the plurality of pixels are assigned the first value.

12. The system of claim 7 further comprising displaying the new digital image.

13. 1. A method for modifying pixel tone values ​​of a digital image, comprising: receiving, at one or more computing devices, a digital image having a plurality of pixels; determining, at the one or more computing devices, a measured luminance value for each of the plurality of pixels; determining, at the one or more computing devices, locations of the plurality of pixels corresponding to the artificial object in the digital image based on the measured luminance values ​​of each of the plurality of pixels; computing, at the one or more computing devices, a tone transform configured to suppress tone of the artificial object in the digital image, the tone transform comprising: measuring at least one pixel tone value of the digital image on the one or more computing devices; analyzing, at the one or more computing devices, the at least one pixel tone value of the digital image to calculate a target pixel tone value based on locations of the plurality of pixels corresponding to the artificial object in the digital image; and adjusting, at the yet another computing device, the at least one pixel tone value of the digital image to the target pixel tone value; applying, at the one or more computing devices, the tone transformation to each of the pixels at the locations of the plurality of pixels corresponding to the artificial object in the digital image to form a new digital image. A method comprising:

14. The method of claim 13 , wherein the at least one pixel tone value is at least one of a maximum pixel tone value, a minimum pixel tone value, and an image histogram.

15. 15. The method of claim 14, wherein the at least one pixel tone value is the image histogram, and the tone transformation further comprises determining an artificial object histogram based on the locations of the plurality of pixels corresponding to the artificial object in the digital image.

16. 16. The method of claim 15, wherein the artificial object histogram has a first window width, the image histogram has a second window width, the first window width has a first window center, and the second window width has a second window center.

17. 17. The method of claim 16, wherein calculating the target pixel tone value includes at least one of adjusting the first window width to be approximately the same as the second window width and adjusting the first window center to be approximately the same as the second window center.

18. 1. A system including one or more processors and a memory coupled to the processors containing instructions executable by the processors, the instructions, when executed by the processor, receiving a digital image having a plurality of pixels; identifying a measured luminance value for each of the plurality of pixels; determining a location of the plurality of pixels corresponding to an artificial object in the digital image based on the measured luminance value of each of the plurality of pixels; calculating a tone transform configured to suppress tone of the artificial object in the digital image, the tone transform comprising: measuring an image histogram of said digital image; analyzing the image histogram to determine an artificial object image histogram based on the locations of the plurality of pixels corresponding to the artificial object in the digital image; instructions for adjusting the artificial object image histogram to form a target image histogram; applying a tone transformation to the locations of the plurality of pixels corresponding to the artificial object in the digital image to form a new digital image; A system capable of operating as follows.

19. 20. The system of claim 18, wherein the tone conversion further comprises measuring a first window width of the artificial object histogram and measuring a second window width of the image histogram, the first window width having a first window center and the second window width having a second window center.

20. 20. The system of claim 19, further comprising adjusting the first window center to be substantially the same as the second window center.

21. 20. The system of claim 19, further comprising adjusting the first window width to be approximately the same as the second window width.

Images