Viewer with automatic opacity adjustment of image mask

Abstract

An apparatus for interacting with one or more digital full slice images (WSIs) acquired by an imaging device includes a display, a memory, and one or more hardware processors. The memory is configured to store computer executable instructions. The one or more hardware processors are in communication with the display and the memory. The one or more hardware processors are configured to drive the display using computer executable instructions of the memory such that the one or more hardware processors are configured to generate a user interface. The user interface includes an image layer and one or more mask layers overlying the image layer. The one or more mask layers have a predetermined opacity level. The one or more hardware processors are also configured to automatically adjust a predetermined opacity level according to a magnification level of the image layer.

Description

[0001] priority

[0002] This application claims priority to U.S. Provisional Application No. 63 / 579,074, filed August 28, 2023, entitled “Viewer with Automatic Opacity Adjustment of Image Mask,” the disclosure of which is incorporated herein by reference. Background Technology

[0003] Microscopic analysis of tissue samples can be performed for various diagnostic purposes, including detecting the presence of cancer by identifying structural abnormalities in the tissue sample. In this analysis, the tissue sample can be embedded and then dissected into multiple individual sections. Each section can then be placed on a separate glass slide. The tissue sections on each slide can be stained to enhance contrast and / or highlight regions of interest. Each slide can then be imaged to form a digital whole-slide image (WSI). Individual digital WSIs can be analyzed to identify structural features in the tissue sample. In some cases, the analysis of such WSIs can be referred to as digital pathology.

[0004] U.S. Patent No. 10,732,394 (issued August 4, 2020, entitled “Managing Plural Scanning Devices in a High-Throughput Laboratory Environment”), U.S. Patent No. 7,738,688 (issued June 15, 2010, entitled “System and Method for Viewing Virtual Slides”), and U.S. Publication No. 2022 / 0309670 (published September 29, 2022, entitled “Method and System for Visualizing Information on Gigapixels Whole Slide Image”) disclose, by way of example only, devices and systems for digital pathology, the disclosures of which are incorporated herein by reference.

[0005] In some cases, combining image analysis with one or more image masks can be beneficial. For example, various forms of artificial intelligence and / or machine learning can be used to generate image masks based on features within one or more images. In one example, such an image mask can be used in conjunction with one or more digital WSIs in a digital pathology environment. In this case, a machine learning diagnostic system can be used to diagnose diseases or other conditions based on histopathological images. Typically, such systems employ artificial intelligence to identify patterns in histopathological images that can be used to generate a diagnosis, which can be graphically illustrated in the form of one or more image masks. Such systems can be combined with traditional human analysis. In other words, such systems can serve as a complement to the human analysis of digital WSIs. Therefore, it is desirable to provide certain user interface features within the digital pathology environment to enable combined digital WSI analysis modalities.

[0006] Although several systems and methods have been manufactured and used to analyze images, it is believed that no one had manufactured or used the invention described in the appended claims before the inventor. Attached Figure Description

[0007] Although the specification concludes with claims that specifically point out and explicitly claim protection for the technology, it is believed that the technology will be better understood by the following description of certain examples in conjunction with the accompanying drawings, in which the same reference numerals denote the same elements, and wherein:

[0008] Figure 1 An exemplary environment for the imaging system is described;

[0009] Figure 2 Exemplary computing systems are described that can implement any one or more of the imaging devices, image analysis systems, user computing devices, interface servers, machine learning servers, and other components described herein;

[0010] Figure 3 Depicting and Figure 1 Imaging systems and Figure 2 An exemplary user interface used in conjunction with a computing system;

[0011] Figure 4 Depicting Figure 3 The user interface, where the image layer is adjusted to a 10x magnification level;

[0012] Figure 5 Depicting Figure 3 The user interface, where the image layer is adjusted to a 20x magnification level;

[0013] Figure 6 Depicting Figure 3 The user interface, where the image layer is adjusted to a 40x magnification level; and

[0014] Figure 7 Depicting Figure 3 A detailed view of the user interface, where the image layer is at a 1x magnification level, and details of one or more mask boundaries are visible; and

[0015] Figure 8 Depicting Figure 3 Another detailed view of the user interface, where the image layer is at a 40x magnification level, and details of one or more mask boundaries are visible.

[0016] The accompanying drawings are not intended to be limiting in any way, and it is conceivable that various embodiments of the technology may be implemented in a variety of other ways, including those not necessarily depicted in the drawings. The drawings, which are incorporated in and form part of this specification, illustrate several aspects of the technology and, together with the specification, serve to explain the principles of the technology; however, it should be understood that the technology is not limited to the precise arrangement shown. Detailed Implementation

[0017] The following description of certain examples of the technology is not intended to limit its scope. Other examples, features, aspects, embodiments, and advantages of the technology will become apparent to those skilled in the art from the following description, which presents by way of illustration one of the best modes contemplated for carrying out the technology. As will be appreciated, the technology described herein is capable of achieving other different and obvious aspects, all without departing from the technology. Therefore, the drawings and descriptions should be considered illustrative in nature, not restrictive.

[0018] I. Overview of Exemplary Imaging Systems

[0019] Figure 1 An exemplary environment (100) (e.g., an imaging system) in which an operator and / or imaging system can analyze a sample is illustrated. The environment (100) includes an automated slide stainer controlled to produce uniformly stained slides based on one or more protocols. The environment (100) may also include an imaging device (102) that generates a digital representation (e.g., an image) of the stained slide. The digital representation may be transmitted as a signal [C] to a network (112) and then to an image analysis system (108) for processing (e.g., feature detection, feature measurement, etc.). The image analysis system (108) may perform image analysis on the received image data. The image analysis system (108) may normalize the acquired image data to input it into a machine learning algorithm and / or model that can determine the features of the image. The results from the image analysis system (108) may be transmitted as a signal [E] to one or more display devices (110) (also referred to herein as “display devices” or “client devices”).

[0020] In some examples, the imaging device (102) includes a light source (104) configured to emit light onto a tissue sample and an imaging sensor (106) configured to detect light emitted from the tissue sample. In some examples, the light source (104) and the imaging sensor (106) may be configured for use with multispectral imaging. In these examples, multispectral imaging using the light source 104 may involve providing light to a tissue sample carried by a carrier within a frequency range. Therefore, the light source (104) may be configured to generate light across the spectrum to provide multispectral imaging.

[0021] In some examples, the tissue sample may reflect light received from the light source (104), and the reflected light can then be detected at the imaging sensor (106). In these examples, the light source (104) and the imaging sensor (106) may be located on substantially the same side of the tissue sample. In other examples, the light source (104) and the imaging sensor (106) may be located on opposite sides of the tissue sample.

[0022] The imaging device (102) is configured to capture and / or generate image data for analysis. To facilitate this functionality, the imaging device (102) may include one or more of a lens, an image sensor, a processor, or a memory. The imaging device (102) may also be configured to receive operator interaction. Operator interaction may be a request to capture image data. Based on operator interaction, the imaging device (102) may capture image data. The imaging device (102) may also be configured to store image data and other information in an information database (113) containing images and other information. The imaging device (102) may also be configured to receive image data from additional imaging devices. For example, the imaging device (102) may be a node that routes image data from other imaging devices to an image analysis system (108). In some examples, the imaging device (102) may be located within the image analysis system (108) as a component therein. In other examples, the imaging device (102) and the image analysis system (108) may communicate with each other (e.g., wireless or wired connection). For example, the imaging device (102) and the image analysis system (108) can communicate via a network (112). In some examples, the image analysis system (108) can be connected to multiple imaging devices (via wired or wireless connections).

[0023] In some examples, the image analysis system (108) communicates with one or more display devices (110). This communication may facilitate operator input or provide recommendations for image datasets. For example, the image analysis system (108) may be configured to send recommendations to the display device (110) via a network (112). In some examples, the image analysis system (108) is configured to operate in conjunction with a computing system (200), which is described in more detail below. As will be described in more detail below, the computing system (200) may be configured to engage and disengage from the image analysis system (108) to receive recommendations. For example, the display device (100) may engage with the image analysis system when it is determined that the image analysis system (108) has generated recommendations for the display device (110). Furthermore, the display device (110) may connect to the image analysis system (108) based on image analysis performed on image data corresponding to a specific computing system (200). For example, a user may associate multiple histological samples. When a specific histological sample is determined to be associated with a specific user and a corresponding display device (110), the image analysis system (108) may send a recommendation of the histological sample to the specific display device (100). In some embodiments, the display device (110) may interface with the image analysis system (108) to receive the recommendation.

[0024] Imaging device (102), image analysis system (108), and / or display device (110) communicate with each other via network (112). Network (112) may include various communication modes, such as wired and / or wireless modes and / or technologies. Network (112) may include personal area networks (“PANs”), local area networks (“LANs”), campus networks (“CANs”), metropolitan area networks (“MANs”), extranets, intranets, the Internet, short-range wireless communication networks (e.g., ZigBee, Bluetooth, etc.), wide area networks (“WANs”) (centralized and / or distributed) and / or any combination, arrangement, and / or aggregation of the above. Network (112) may include and / or be accessible from and / or originate from the Internet.

[0025] Imaging device (102) and image analysis system (108) are configured to transmit image data. For example, imaging device (102) is configured to transmit image data associated with a histological sample to image analysis system (108) for analysis via network (112). Image analysis system (108) and display device (110) are configured to transmit recommendations corresponding to the image data. For example, image analysis system (108) may transmit a diagnosis regarding whether the image data indicates the presence of a disease in the tissue sample. In some examples, imaging device (102) and image analysis system (108) are configured to communicate via a first network, and image analysis system (108) and display device (110) are configured to communicate via a second network. In other examples, imaging device (102), image analysis system (108), and display device (110) may communicate via the same network (112).

[0026] The environment (100) also includes one or more computer systems (115) (“computer system 115”) configured to communicate with the imaging device (102), the image analysis system (108), and / or the display device (110). In some examples, the computer system (115) is configured to communicate directly with the imaging device (102), the image analysis system (108), and / or the display device (110) via a network (112).

[0027] In some examples, the computer system (115) is configured to provide information to change the function or operation of the imaging device 102, the image analysis system (108), the display device (110), and / or the network (112). For example, the information may be new software, software updates, new or revised lookup tables, or data or any other type of information used in any way to generate, manipulate, transmit, or render (for convenience, collectively referred to herein as "update") an image. Updates may relate to, for example, image compression, image transmission, image storage, image display, image rendering, etc. In some examples, the computer system (115) is configured to provide a message to the device or system to be updated, or to provide a message to a user interacting with system controls to update the system. In some examples, updates are provided automatically, such as periodically or as needed / as available. In other examples, updates are provided in response to receiving an instruction to provide an update from an operator (e.g., confirmation of an update or a request for an update).

[0028] exist Figure 1In the example shown, in [A], the imaging device (102) can acquire block data. To acquire block data, the imaging device (102) can image the tissue block (e.g., scan, capture, record, etc.). The tissue block can be a histological sample. For example, the tissue block can be a biological tissue block that has been removed and is ready for analysis. As will be described in more detail below, various histological techniques can be performed on the tissue block to prepare it for analysis. The imaging device (102) can capture an image of the tissue block and store the corresponding block data in the imaging device (102). The imaging device (102) can acquire block data based on user interaction. For example, a user can provide input through a user interface (e.g., a graphical user interface (“GUI”)) and request the imaging device (102) to image the tissue block. Alternatively, a user can interact with the imaging device (102) to enable the imaging device (102) to image the tissue block. For example, a user can toggle the imaging device (102) on / off, press a button on the imaging device (102), provide a voice command to the imaging device (102), or otherwise interact with the imaging device (105) to enable the imaging device (102) to image the tissue block. In some examples, the imaging device (102) can image the tissue block based on the imaging device (102) detecting that the tissue block has been placed in the viewport of the imaging device (102). For example, the imaging device (102) can determine that the tissue block has been placed in the viewport of the imaging device (102) and image the tissue block based on that determination.

[0029] In [B], the imaging device (102) acquires slice data. In some examples, the imaging device (102) is configured to acquire both slice data and block data at this stage. In other examples, a first imaging device (102) may acquire slices, and a second imaging device (102) may acquire block data. To acquire slice data, the imaging device (102) may image (e.g., scan, capture, record, etc.) slices of a tissue block. Slices of a tissue block may be slices of a histological sample. For example, a tissue block may be sliced ​​(e.g., dissected) to generate one or more slices of the tissue block. In some examples, a portion of a tissue block may be sliced ​​to generate slices of the tissue block, such that a first portion of the tissue block corresponds to a tissue block imaged to acquire block data, and a second portion of the tissue block corresponds to a slice of the tissue block imaged to acquire slice data. The imaging device (102) may capture images of the slices and store the corresponding slice data in the imaging device (102). In some examples, the imaging device (102) is configured to acquire slice data based on user interaction. For example, a user can provide input through a user interface and request the imaging device (102) to image the slice. Alternatively, the user can interact with the imaging device (102) to image the slice. In other examples, the imaging device (102) is configured to image the tissue block based on the imaging apparatus (103) detecting that the tissue block has been sliced ​​or that the slice has been placed in the viewport of the imaging device (102).

[0030] In [C], the imaging device (102) is configured to send a signal representing captured image data (e.g., block data and slice data) to the image analysis system (108). Specifically, the imaging device (102) is configured to transmit the captured image data as an electronic signal to the image analysis system (108) via a network (112). This signal may include and / or correspond to pixel representations of the block data and / or slice data. It should be understood that the signal may include and / or correspond to more, fewer, or different image data. For example, the signal may correspond to multiple slices of a tissue block and may represent first slice data and second slice data. Furthermore, the signal may enable the image analysis system (108) to reconstruct the block data and / or slice data. In some examples, the imaging device (102) may send a first signal corresponding to the block data and a second signal corresponding to the slice data. In other examples, a first imaging device may send a signal corresponding to the block data, and a second imaging device may send a signal corresponding to the slice data.

[0031] In [D], the image analysis system (108) is configured to perform image analysis on block data and slice data provided by the imaging device (102). In this example, the image analysis system (108) is configured to perform one or more image processing functions. For example, the image analysis system (108) is configured to perform one or more imaging algorithms. In some examples, the image analysis system (108) is configured to perform the image processing functions using a machine learning model (e.g., a convolutional neural network). Based on the execution of the image processing functions, the image analysis system (108) can determine the probability that the block data and slice data correspond to the same tissue block. For example, in some examples, the image processing functions include performing edge analysis on the block data and slice data. Based on such edge analysis, the image analysis system (108) is configured to determine whether the block data and slice data correspond to the same tissue block. In some examples, the image analysis system (108) is configured to determine a confidence threshold based on the response of the display device (110) to a specific recommendation. Furthermore, the confidence threshold can be specific to a user, a group of users, the type of tissue block, the location of the tissue block, or any other factor. In these examples, the image analysis system (108) is configured to compare a determined confidence threshold with the performed image analysis. Based on this comparison, the image analysis system (108) can generate recommendations instructing the display device (110) on actions based on the probability that block data and slice data correspond to the same tissue block. In other examples, the image analysis system (108) is configured to provide a diagnosis, for example, based on the results of a machine learning algorithm, regarding whether the image data indicates the presence of a disease in the tissue sample.

[0032] In [E], the image analysis system (108) is configured to transmit signals to the display device (110). Specifically, the image analysis system (108) is configured to send the signals as electrical signals to the display device (110) via a network (112). The signals may include and / or correspond to a diagnosis. Based on the received signals, the display device (110) can determine a diagnosis. In some examples, the image analysis system (108) may send a series of recommendations corresponding to a set of tissue blocks and / or a set of slides. The image analysis system (108) may include recommended actions from the user in the recommendations. For example, the recommendations may include recommending that the user view the tissue blocks and slides. Furthermore, the recommendations may include recommending that the user does not need to view the tissue blocks and slides.

[0033] II. Exemplary Computing System

[0034] Figure 2 An exemplary computing system (200) is illustrated. In various examples, this computing system (200) can implement the functionality of one or more devices described herein, such as... Figure 1The imaging system (100) shown includes an imaging device (102), an image analysis system (108), and / or a display device (110). As shown, the computing system (200) includes one or more hardware processors (202) (such as a physical central processing unit (“CPU”), one or more network interfaces (204) (such as a network interface card (“NIC”), and one or more computer-readable media (206). In some examples, the computer-readable media (206) includes, for example, a high-density disk (“HDD”), a solid-state drive (“SDD”), a flash drive, and / or other persistent non-transient computer-readable media. The computing system (200) optionally includes an input / output device interface (208), such as an input / output (“IO”) interface for communicating with one or more microphones, and one or more non-transient computer-readable memories (or “media”) (210), such as random access memory (“RAM”) and / or other volatile non-transient computer-readable media.

[0035] The network interface (204) is configured to provide connectivity to one or more networks or computing systems. The hardware processor (202) is configured to receive information instructions from other computing systems or services via the network interface (204). The network interface (204) can also directly store data into a computer-readable storage device (210). The hardware processor (202) can communicate bidirectionally with the computer-readable storage device (210). The hardware processor (202) can execute instructions and process data in the computer-readable storage device (210).

[0036] The computer-readable storage medium (210) is configured to store one or more computer program instructions, and the hardware processor (202) is configured to execute one or more computer program instructions to implement one or more of the examples described herein. The computer-readable storage medium (210) is also configured to store other computer program instructions, such as an operating system (212). The operating system (212) and / or other associated computer program instructions are configured to provide computer program instructions for use by the computer processor (202) in the overall management and operation of the computing system (200). The computer-readable storage medium (210) may also include program instructions and other information for implementing aspects of this disclosure. In one example, the computer-readable storage medium (210) includes instructions for training and / or executing a machine learning model (214). In other examples, the computer-readable storage medium (210) may include image data (216). In yet another example, the computer-readable storage medium (210) includes instructions for classifying one or more images based on a trained machine learning model (214).

[0037] II. Exemplary User Interface for Analyzing Digital WSI

[0038] As described above, the environment or imaging system (100) is configured to perform image analysis on received image data. In some cases, it may be desirable to combine the environment (100) with certain user interface features to facilitate interaction between the user, the image data, and any image analysis performed by the image analysis system (108). In some cases, such image analysis may include outputting machine learning algorithms and / or models to facilitate the identification of various features of one or more images. Such output can be used in conjunction with user-based analysis modalities, such as direct visualization of image data by the user. Therefore, it may be desirable to include certain user interface features within the environment (100) to facilitate interaction between image analysis performed by the image analysis system (108) and user-based analysis modalities.

[0039] Figures 3 to 6 An exemplary user interface (400) (also known as a graphical user interface) for use with the aforementioned environment (100) and / or computing system (200) is shown. For example, one or more display devices (110) may be configured to display the user interface (400). By way of example only, the display device (110) for displaying the user interface (400) may be integrated into a user workstation, such as a network-connected personal computer. Thus, in some examples, the user interface (400) is configured to be remotely operated by the user relative to other components of the environment (100), such as imaging equipment (102) and / or image analysis system (108).

[0040] The user interface (400) is typically configured to facilitate viewing and manipulating one or more digital whole-slice images (WSIs) acquired using the imaging device (102). Therefore, the user interface (400) includes a display pane (410) for displaying one or more digital WSIs and a tool pane (440) for manipulating one or more digital WSIs. As will be described in more detail below, the display pane (410) is configured to show various layers (460, 480) that can be used to present one or more digital WSIs with different levels of abstraction to the user.

[0041] The tool pane (440) includes a zoom button (442), a measurement button (444), an opacity slider (448), and one or more mask selection checkboxes (450). Features of the tool pane (440) are typically driven by one or more computing systems (such as the aforementioned computing systems (115, 200)). Specifically, features of the tool pane (440), described in more detail below, can be manipulated by a user via a display (such as a monitor (110)) in conjunction with one or more user input features (such as a touchscreen, mouse, touchpad, etc.). Such a computing system can then receive such user input and manipulate the display of one or more digital WSIs presented in the display pane (410). Therefore, the tool pane (440) and the display pane (410) can be used in conjunction with one or more processors, memory, and / or other components to facilitate manipulation of one or more digital WSIs via the tool pane (440) and their presentation on the display pane (410).

[0042] The zoom button (442) is typically configured to manipulate one or more digital WSIs through a series of zoom levels. For example, when a user selects the zoom button (442), the zoom button (442) can manipulate a specific digital WSI through multiple zoom levels (such as 1X, 10X, 20X, and 40X), with each successive selection progressing from one zoom level to another. Optionally, the zoom button (442) also includes a zoom level indicator configured to convey a specific zoom level shown in the display pane (410). In this example, the zoom level indicator is shown as a text box. In other examples, the zoom level indicator may take various alternative forms, such as a graphical level gauge. Although the zoom button (442) is shown as a graphical button in this example, it should be understood that in other examples, the zoom button (442) may have various alternative configurations. For example, in some examples, the zoom button (442) takes the form of a graphical slider, configured to allow adjustment of the zoom level and simultaneously indicate the level graphically on a graphical representation.

[0043] The Measurement button (444) is typically configured to activate a measurement utility function that can be used to measure distances between various features in a digital WSI. In this example, the Measurement button (444) is positioned between the Zoom button (442) and the Opacity slider (448), although various other positions may be used in other examples. Upon selection of the Measurement button 444, it is configured to initiate a measurement utility sequence using a calculation system such as the calculation system (115, 200) described above. Once initiated, a stylized cursor (e.g., a crosshair) appears to indicate to the user that they can select one or more features in the digital WSI. Once one or more such features are selected, other features can be selected to measure distances from one feature to another. Of course, in other examples, the specific implementation of the measurement utility sequence may vary in accordance with the teachings herein, as will be apparent to those skilled in the art.

[0044] As will be described in more detail below, the opacity slider (448) is typically configured to selectively adjust the appearance of one or more masks or other overlay features set on one or more digital WSIs. The opacity slider (448) includes a graphic slider and an opacity level indicator adjacent to the graphic slider. The graphic slider is configured to be dragged along a linear continuum to selectively adjust the opacity from 1% to 100%. The opacity level indicator is configured to display a numerical indication of the opacity selected by the graphic slider. Although the opacity slider (448) is described herein as being used in conjunction with an image feature of opacity, it should be understood that in other examples, different image features may be adjusted using a graphic slider substantially similar to the graphic slider of the opacity slider. Furthermore, in other examples, the opacity slider (448) may be combined with other graphic sliders to adjust different image features simultaneously.

[0045] Mask selection checkboxes (450) are typically configured to enable and disable the appearance of certain masks or other overlay features set on one or more digital WSIs, as will be discussed in more detail below. Each mask selection checkbox (450) includes a graphical checkbox and a label. Each corresponding checkbox is configured to selectively enable and disable the appearance of a given mask or other overlay feature. Each corresponding checkbox is also configured to indicate the enabled or disabled state by graphically displaying a check mark, an "X," or other indicator. Each corresponding label includes text to identify which mask selection checkbox (450) corresponds to a given mask or other overlay feature. Thus, each mask selection checkbox (450) is configured for graphical selection by the user to toggle one or more masks or other overlay features between enabled and disabled states. While the mask selection checkboxes (450) in this example include two mask selection checkboxes (450), it should be understood that any suitable number of mask checkboxes (450) may be used in other examples.

[0046] As described above, the display pane (410) is configured to display various layers (460, 480) that can be used to present one or more digital WSIs to the user. Specifically, the display pane (410) includes an image layer (460) overlaid with one or more mask layers (480). The image layer (460) is generally configured to present one or more basic, non-abstract digital WSIs to the user within the display pane (410). In some examples, the non-abstract nature of the image layer (460) may correspond to the raw digital image output produced by the imaging device (102). In other examples, the non-abstract nature of the image layer (460) may include some image processing relative to the raw digital image output produced by the imaging device (102). For example, such image processing may be performed by the imaging device (102) itself or by other components of the imaging system (100), such as an image analysis system (108) . Such image processing may include, for example, edge analysis to remove disorganized areas from the image, contrast and sharpness adjustments, color adjustments, focus adjustments, etc.

[0047] A mask layer (480) is typically configured to help a user identify a specific region of interest within one or more digital WSIs. Therefore, the mask layer (480) overlays the image layer (460), and its opacity or transparency is adjustable to allow viewing of one or more masks (482, 484) while viewing the content of the image layer (460). In other words, the mask layer (480) is typically configured to highlight a specific region of interest within one or more digital WSIs. For example, the mask layer (480) includes one or more masks (482, 484) that can be generated using artificial intelligence (AI) or machine learning algorithms implemented by the aforementioned image analysis system (108) and / or one or more computing systems (115, 200). By way of example only, such an algorithm could include an AI vision algorithm configured to operate as predictive AI to identify tissue structures that may indicate the presence of cancer or other pathologies. This identification can then be mapped to one or more digital WSIs and presented to the user as one or more masks (482, 484).

[0048] In this example, the masks (482, 484) include a first mask (482) corresponding to one structure of interest and a second mask (484) corresponding to another structure of interest. Specifically, the first mask (482) corresponds to an tissue structure identified by the aforementioned AI or machine learning algorithm as having one or more predetermined features (e.g., possibly an invasive tissue structure). Meanwhile, the second mask (484) corresponds to an tissue structure identified by the aforementioned AI or machine learning algorithm as having one or more alternative predetermined features or combinations of features (e.g., possibly low-grade ductal carcinoma (DCIS) and / or atypical ductal hyperplasia (ADH)). In some examples, the tissue structures identified by the aforementioned AI or machine learning algorithm may overlap with each other. For example, some tissue structures identified as having a feature associated with the first mask (482) may also be identified as having a feature associated with the second mask (484). Therefore, in some examples, the mask (482, 484) can be organized in a separate mask layer (480), and when two masks (482, 484) could originally be displayed at the same time, one mask (482, 484) has a higher display priority than the other mask (484, 482).

[0049] As described above, the opacity slider (448) is typically configured to selectively adjust the appearance of one or more masks or other overlay features set on one or more digital WSIs. Therefore, in this example, the opacity slider (448) is configured to control the appearance of the masks (482, 484) to selectively adjust their appearance. Specifically, the opacity slider (448) is configured to adjust the opacity of each mask (482, 484) from 0% (invisible or completely transparent) to 100% (fully visible or completely opaque). In this example, the opacity slider (448) is configured to adjust the opacity of two masks (482, 484) simultaneously. In other examples, the opacity slider (448) is configured to adjust the opacity of a single mask (482, 484) at a time. In these examples, the tool pane (440) may include toggles or other user interface functions to facilitate switching adjustments from one mask (482, 484) to another. In another example, multiple sliders that are essentially similar to the opacity slider (448) are used, so that each mask (482, 484) has a dedicated adjustment in the tool pane (440).

[0050] As described above, the mask selection checkbox (450) is typically configured to enable and disable the appearance of certain masks or other overlay features set on one or more digital WSIs. Therefore, in this example, the mask selection checkbox (450) is configured to enable and disable the appearance of masks (482, 484). Specifically, the first mask box (452) is configured to enable and disable the first mask (482), while the second mask box (454) is configured to enable and disable the second mask (484). Thus, each mask box (452, 454) can operate independently of the other mask box (452, 454) to control whether the first mask (482) and the second mask (484) are visible.

[0051] For illustrative purposes, each mask (482, 484) in this example is shown with a crosshair in the black-and-white line drawing. Although crosshairs are used in some examples, the crosshairs shown in this example represent the coloring of each mask (482, 484). In particular, each mask (482, 484) can be a different solid color from the other mask (484, 482). By way of example only, the first mask (482) could be red or another similar color, while the second mask (484) could be green or another similar color. In other examples, various alternative colors can be used to facilitate differentiation between masks (482, 484). Furthermore, in some examples, the tool pane (440) may include a color palette, allowing the user to select a specific color for each mask (482, 484).

[0052] Each mask (482, 484) includes a corresponding mask boundary (483, 485) surrounding the perimeter of each respective mask (482, 484). Each mask boundary (483, 485) is configured to have a different appearance relative to the interior of the corresponding mask (482, 484) to highlight the boundaries between different masks (482, 484) and / or areas where no mask exists. This feature can be particularly desirable when, at relatively high magnification, the entirety of a given mask (482, 484) may be invisible. In this example, each mask boundary (483, 485) is shown using dashed lines to represent the appearance difference between each mask boundary (483, 484) and the corresponding mask (482, 484). In practice, this appearance difference is the difference in opacity between each mask boundary (483, 485) and each corresponding mask (482, 484). In other examples, the difference is a difference in color (e.g., different shades of similar colors or completely different colors). In still other examples, the difference is a difference in line style, such as using the dashed lines shown. In yet another example, various appearance variations can be combined to distinguish the mask boundary (483, 485) from the mask (482, 484).

[0053] like Figures 3 to 8 As shown, the user interface (400) is typically configured to alter the appearance of the masks (482, 484) and / or mask boundaries (483, 485) when switching between different magnification levels. Specifically, the user interface (400) (driven by the processor, imaging analysis system (109), and / or computing system (115, 200)) is configured to automatically adjust the opacity of each mask (482, 484) when switching from one magnification level to another. In this example, the opacity of each mask (482, 484) is adjusted inversely relative to the magnification. In other words, the opacity decreases as the magnification level increases. This inverse relationship is typically needed to reduce the level of abstraction of the image layer (460) as the magnification increases. In particular, at relatively low magnification levels, a higher degree of image abstraction may be required because fine organizational details may be less suitable for analysis, while the external information provided by the masks (482, 484) may be more important. At relatively high magnification levels, lower levels of image abstraction may be more suitable for analyzing fine organizational details. By automatically applying this inverse relationship, higher analysis efficiency can be achieved.

[0054] Figure 3The user interface (400) is shown when the display pane (410) includes the digital WSI at 1X magnification, as can be seen from the magnification indicator of the magnification button (442). Furthermore, the first mask (482) and the second mask (484) are visible because the first mask box (452) and the second mask box (454) are selected in the mask selection checkboxes (450) of the tool pane (440). At 1X magnification, the opacity of both masks (482, 484) is set directly by the opacity slider (448). In some examples, the opacity setting at 1X magnification may correspond to a preferred opacity, which may be stored and retained in memory, such as the aforementioned computer-readable medium (206), for later use. In some examples, such a preferred opacity is set by the user. In other examples, this preferred opacity is set for multiple users at the tenant level. In any case, in this example, the opacity is initially set to 50%. Therefore, the mask (482, 484) at 1x magnification is either 50% visible or 50% transparent. While this article uses a 50% opacity setting, in other examples, any other suitable opacity setting can be used at 1x magnification. For example, in some examples, an opacity setting of 35% could be used.

[0055] Figure 4 The user interface (400) is shown when the display pane (410) includes a digital WSI at 10X magnification, as can be seen via the magnification indicator of the magnification button (442). Furthermore, the first mask (482) and the second mask (484) are visible because the first mask box (452) and the second mask box (454) are selected in the mask selection checkboxes (450) of the tool pane (440). At 10X magnification, the opacity of the two masks (482, 484) relative to... Figure 3 The opacity of the 1X magnification shown is automatically adjusted. Specifically, this automatic adjustment is... Figure 4 The figure shown is relative to Figure 3 The widened crosshair is shown. Due to automatic adjustment, the opacity slider (448) continues to show the opacity setting at 1X magnification, or in some examples, the preferred opacity.

[0056] When switching from 1x magnification to 10x magnification, the opacity can be adjusted in several increments. For example, in this example, the opacity is automatically adjusted by 25% relative to the opacity setting at 1x magnification. In other words, the opacity is reduced to 37.5% at 10x magnification, while it is reduced to 50% at 1x magnification. Therefore, the mask (482, 484) at 10x magnification is 37.5% visible and 62.5% transparent. In examples where the opacity setting at 1x magnification differs from 50%, the same percentage-based reduction can be applied. For example, if an opacity setting of 35% is used at 1x magnification, the opacity setting might be reduced by 25% to 26.25%. In other examples, the opacity setting can be reduced by an absolute reduction of 25 percentage points. Therefore, if an opacity setting of 35% is used at 1x magnification, the opacity setting could be reduced to 10% (35% minus 25%). In other examples, the opacity setting at 10x magnification can be independent of the opacity setting at 1x magnification. Therefore, in these examples, a fixed opacity setting (e.g., 37.5%) can be used at 10x magnification, regardless of the opacity setting at 1x magnification.

[0057] Figure 5 The user interface (400) is shown when the display pane (410) includes the digital WSI at 20X magnification, as can be seen via the magnification indicator of the magnification button (442). Furthermore, the first mask (482) and the second mask (484) are visible because the first mask box (452) and the second mask box (454) are selected in the mask selection checkboxes (450) of the tool pane (440). At 20X magnification, the opacities of the two masks (482, 484) are respectively relative to... Figure 3 and Figure 4 The opacity of the 1X and 10X magnification settings shown is automatically adjusted. Specifically, this automatic adjustment is achieved by... Figure 5 The figure shown is relative to Figure 3 and Figure 4 The widened cross shadow shown is illustrated. Due to automatic adjustment, the opacity slider (448) continues to show the opacity setting at 1X magnification, or in some examples, the preferred opacity.

[0058] When switching between 1X and 20X magnification, or between 10X and 20X, the opacity can be adjusted in several increments. For example, in this example, the opacity is automatically adjusted by 50% relative to the opacity setting at 1X magnification. In other words, the opacity at 20X magnification is reduced to 25%, while the opacity at 1X magnification is reduced to 50%. Therefore, the mask (482, 484) at 20X magnification is 25% visible or 75% transparent. In examples where the 1X opacity setting differs from 50%, the same percentage-based reduction can be applied. For example, if an opacity setting of 35% is used at 1X magnification, the opacity setting might be reduced by 50% to 17.5%. In other examples, the reduction in opacity setting could be an absolute reduction of 30 percentage points relative to the opacity setting at 1X magnification. Therefore, if an opacity setting of 35% is used at 1X magnification, the opacity setting at 20X magnification might be reduced to 5%. In other examples, the opacity setting at 10x magnification can be independent of the opacity setting at 1x magnification. Therefore, in these examples, an opacity setting of 25% can be used at 20x magnification, regardless of the opacity setting at 1x magnification.

[0059] Figure 6 The user interface (400) is shown when the display pane (410) includes the digital WSI at 40X magnification, as can be seen via the magnification indicator of the magnification button (442). Furthermore, the first mask (482) and the second mask (484) are visible because the first mask box (452) and the second mask box (454) are selected in the mask selection checkboxes (450) of the tool pane (440). At 40X magnification, the opacities of the two masks (482, 484) are respectively relative to... Figures 3 to 5 The 1X, 10X, and 20X magnification settings shown are automatically adjusted. Specifically, this automatic adjustment is performed by... Figure 6 The figure shown is relative to Figures 3 to 5 The widened cross shadow shown is illustrated. Due to automatic adjustment, the opacity slider (448) continues to show the opacity setting at 1X magnification, or in some examples, the preferred opacity.

[0060] When transitioning from 1X to 40X, from 10X to 40X, or from 20X to 40X, the opacity can be adjusted in several increments. For example, in this example, the opacity is automatically adjusted to the minimum opacity setting. Specifically, the 40X magnification in this example typically corresponds to the highest magnification level. Therefore, at 40X magnification, the opacity is adjusted to a 0% opacity setting to minimize the abstraction of the image layer (460). Although a 0% opacity setting is used at 40X magnification in this example, it should be understood that in other examples, at least some non-zero opacity settings (e.g., 1% to 10% opacity) may be used. In these examples, non-zero opacity settings may be needed to provide some visibility of the mask (482, 484) while also minimizing the abstraction of the image layer (460).

[0061] As described above, the user interface (400) (driven by the processor, imaging analysis system (109), and / or computing system (115, 200)) is configured to automatically adjust the opacity of each mask (482, 484) as the magnification level changes from one to another. While certain specific opacity adjustment magnitudes have been described above for different magnification levels, it should be understood that this degree of opacity adjustment may vary in other examples. For example, as described above, in some examples, a percentage adjustment may be used for each given magnification level relative to the opacity level set at 1X magnification. In some examples, the percentage adjustment may be generalized across all magnification levels. Thus, the opacity decreases by 25% with each increase in magnification, 25% at 10X magnification, 25% at 20X magnification (relative to the opacity at 10X magnification), and another 25% at 40X magnification (relative to the opacity at 20X magnification). In other examples, the percentage adjustment may vary for each magnification level according to a predetermined relationship. For example, in some examples, the percentage adjustment may be higher at lower magnification levels and lower at higher magnification levels, thus creating a gradually changing opacity adjustment pattern. Of course, given the teachings of this document, other suitable opacity adjustment pattern will be apparent to those skilled in the art.

[0062] While the appearance of each mask (482, 484) is generally controlled according to the zoom level and initial or preferred opacity settings as described above, it should be understood that in some examples, one or more portions of each mask (482, 484) are controlled independently of the other portions of each mask (482, 484). For example, as... Figure 7 and Figure 8As shown, the mask boundaries (483, 485) behave differently at different zoom levels than the internal regions of each mask (482, 484). In other words, the appearance of the mask boundaries (483, 485) is controlled by a set of rules executed by the processor that are different from the internal regions of the mask (482, 484).

[0063] In this example, regardless of the magnification level, the two mask boundaries (483, 485) exhibit the same opacity. For example, Figure 7 The appearance of the mask boundaries (483, 485) at a 1x magnification level is shown, while Figure 8 The appearance of the mask boundaries at a 40X magnification level is shown. As illustrated, the opacity of the mask boundaries (483, 485) remains substantially similar between the two magnification levels, as indicated by the substantially similar dashed appearance of each corresponding mask boundary (483, 485). It should be understood that in this example, each mask boundary (483, 485) is shown as a dashed line for illustrative purposes only; in practice, each mask boundary (483, 485) could be in the form of one or more solid lines.

[0064] The opacity of the mask boundary (483, 485) can be set in various ways. For example, in this example, the opacity setting of the mask boundary (483, 485) is a relatively high preset setting. As an example only, the opacity setting of the mask boundary (483, 485) can be preset to 50% to 90% opacity. This preset opacity can also be fixed at the user level. In other examples, the opacity setting of the mask boundary (483, 485) is a function of the initial or preferred opacity setting at a 1X magnification level. In these examples, the opacity setting of the mask boundary (483, 485) is essentially similar to the initial or preferred opacity setting. In other examples, the opacity setting of the mask boundary (483, 485) is a function of the initial or preferred opacity setting, and the opacity setting of the mask boundary (483, 485) is a modified version of the initial or preferred opacity setting.

[0065] Although this example uses a fixed opacity setting for the mask boundaries (483, 485) across different magnification levels, it should be understood that in other examples, the opacity setting of the mask boundaries (483, 485) can vary between magnification levels. For example, in some examples, the opacity of the mask boundaries (483, 485) can vary in a manner substantially similar to the inner area of ​​the mask (482, 484) as described above. As mentioned above, the opacity of the mask boundaries (483, 485) is initially set to 1x magnification level. This initial opacity setting is then modified at each magnification level. In other examples, the opacity setting of the mask boundaries (483, 485) is adjusted according to the magnification level, similar to the mask (482, 484), but at a different rate. For example, the adjustment of the opacity setting of the mask boundaries (483, 485) may not be significant relative to the adjustment of each corresponding mask (482, 484). Therefore, the mask boundary (483, 485) may be easier to identify than the mask (482, 484). Generally, it may be expected that the mask boundary (483, 485) has higher visibility than the mask (482, 484) to provide information associated with the mask (482, 484) while still reducing the image abstraction associated with the mask (482, 484).

[0066] Although the opacity of the mask boundaries (483, 485) remains substantially similar across magnification levels in this example, it should be understood that other characteristics of the mask boundaries (483, 485) may vary with magnification levels even if the opacity remains consistent. For example, in some examples, the line width or thickness of each mask boundary (483, 485) may be adjusted according to the magnification level. In some examples, the line width of each mask boundary (483, 485) increases at lower magnification levels and decreases at higher magnification levels, and vice versa. In these examples, it may be necessary to adjust the line width to scale the appearance of each mask boundary (483, 485) to the appearance of the image layer (460). Furthermore, or alternatively, in some examples, each mask boundary (483, 485) may toggle between solid and dashed lines or between solid and dashed lines. Of course, given the teachings of this paper, various additional variations in the characteristics of the mask boundaries (483, 485) will be apparent to those skilled in the art.

[0067] III. Exemplary Combinations

[0068] The following examples illustrate various non-exhaustive ways in which the teachings herein can be combined or applied. It should be understood that the following examples are not intended to limit the scope of any claims that may be raised at any time in this application or in subsequent filings thereof. No waiver of rights is constituted. The following examples are provided for illustrative purposes only. It is conceivable that the various teachings herein may be arranged and applied in many other ways. It is also conceivable that some variations may omit certain features mentioned in the following examples. Therefore, no aspect or feature mentioned below should be considered critical unless expressly indicated subsequently by the inventor or a successor to the inventor's rights. If any claim is raised in this application or in a related subsequent filing that includes features beyond those described below, it should not be presumed that such additional features were added for any reason related to patentability.

[0069] Example 1

[0070] An apparatus for interacting with one or more digital whole-slice images (WSI) acquired by an imaging device, the apparatus comprising: a display; a memory configured to store computer-executable instructions; and one or more hardware processors in communication with the display and the memory, wherein the one or more hardware processors are configured to drive the display using the computer-executable instructions of the memory, such that the one or more hardware processors are configured to: generate a user interface including an image layer and one or more mask layers overlaying the image layer, the one or more mask layers having a predetermined opacity level and automatically adjusting the predetermined opacity level according to the magnification level of the image layer.

[0071] Example 2

[0072] According to the apparatus of Example 1, one or more hardware processors are further configured to adjust a predetermined opacity level in a manner indirectly proportional to the magnification level of the image layer.

[0073] Example 3

[0074] According to the apparatus of Example 1 or 2, one or more mask layers include a first mask and a second mask, and one or more hardware processors are further configured to adjust the opacity of the first mask and the second mask simultaneously.

[0075] Example 4

[0076] According to any of the apparatuses in Examples 1 to 3, one or more mask layers include a first mask and a second mask, wherein the first mask has a different color relative to the second mask.

[0077] Example 5

[0078] According to the device in Example 4, different colors are selectable by the user.

[0079] Example 6

[0080] According to the apparatus of any one of Examples 1 to 5, one or more hardware processors are further configured to: analyze one or more features of one or more digital WSIs to generate one or more regions of interest within one or more digital WSIs, and generate one or more mask layers based on the one or more regions of interest.

[0081] Example 7

[0082] According to the apparatus of Example 6, a predictive artificial intelligence algorithm is used to perform analysis on one or more features of one or more digital WSIs.

[0083] Example 8

[0084] According to the apparatus of any one of Examples 1 to 7, one or more hardware processors are further configured to: generate one or more boundary lines associated with each of the one or more mask layers, and maintain one or more boundary lines at a consistent opacity depending on the magnification level of the image layer.

[0085] Example 9

[0086] According to the apparatus of any one of Examples 1 to 7, one or more hardware processors are further configured to: generate one or more boundary lines associated with each of the one or more mask layers, and maintain a different appearance of the one or more boundary lines relative to one or more portions of the one or more mask layers, depending on the magnification level of the image layer.

[0087] Example 10

[0088] According to any of the apparatuses in Examples 1 to 7, one or more hardware processors are further configured to: generate one or more boundary lines associated with each of the one or more mask layers, and adjust the opacity of one or more boundary lines according to the magnification level of the image layer.

[0089] Example 11

[0090] According to the apparatus of any one of claims 1 to 7, one or more hardware processors are further configured to: generate one or more boundary lines associated with each of the one or more mask layers, and adjust the opacity of one or more boundary lines according to the magnification level of the image layer, wherein the adjustment of the opacity of one or more boundary lines is different from the adjustment of a predetermined opacity level of the one or more mask layers.

[0091] Example 12

[0092] According to any of the devices in Examples 1 to 11, the predetermined opacity level corresponds to the preferred opacity level.

[0093] Example 13

[0094] According to the device in Example 12, the preferred opacity level is user-selectable at the 1x magnification level.

[0095] Example 14

[0096] According to the device in Example 12, the preferred opacity level is set at the tenant level.

[0097] Example 15

[0098] The apparatus according to any one of Examples 1 to 14 further includes a network interface that communicates with a network to receive one or more digital WSIs from the imaging device.

[0099] Example 16

[0100] A non-transient computer-readable medium having instructions stored thereon, wherein when the instructions are executed by at least one hardware processor of the system, the system causes to: acquire one or more digital whole-slice images (WSIs) from an imaging device, the digital WSIs including one or more tissue structures; identify one or more regions of interest within the one or more tissue structures; generate a graphical user interface including an image layer and one or more mask layers, the one or more mask layers including at least one mask covering the image layer and corresponding to the one or more regions of interest; and automatically adjust the opacity of the mask according to the magnification level of the image layer.

[0101] Example 17

[0102] According to the non-transient computer-readable medium of Example 16, the adjustment of the mask opacity is inversely proportional to the magnification level of the image layer.

[0103] Example 18

[0104] According to the non-transient computer-readable medium of Example 16, the adjustment of the mask's opacity is made relative to a preferred opacity level, which is user-selectable.

[0105] Example 19

[0106] According to the non-transient computer-readable medium of Example 16, adjusting the opacity of the mask includes reducing the opacity by 25% relative to the preferred opacity level.

[0107] Example 20

[0108] A method for presenting one or more digital whole-slice images (WSIs) to a user using a graphical user interface, the method comprising: receiving one or more digital WSIs from an imaging device; generating a graphical user interface including an image layer depicting the one or more digital WSIs and a mask layer, the mask layer including a mask covering the image layer; setting a preferred opacity level corresponding to the mask; adjusting the magnification level of the one or more digital WSIs depicted in the image layer; and automatically adjusting the preferred opacity level based on the adjustment of the magnification level of the one or more digital WSIs.

[0109] IV. Summary

[0110] It should be understood that any patent, publication, or other disclosed material, whether in whole or in part, that is said to be incorporated herein by reference, is incorporated herein only if the incorporated material does not conflict with any existing definitions, statements, or other disclosed material set forth in this disclosure. Therefore, to the extent necessary, the disclosure expressly set forth herein supersedes any conflicting material incorporated herein by reference. Any material or part thereof, that is said to be incorporated herein by reference but conflicts with any existing definitions, statements, or other disclosed material set forth herein, is incorporated herein only if there is no conflict between the incorporated material and any existing disclosed material.

[0111] Having illustrated and described various embodiments of the invention, further modifications to the methods and systems described herein can be made by those skilled in the art through appropriate modifications without departing from the scope of the invention. Several such potential modifications have been mentioned, and others will be apparent to those skilled in the art. For example, the examples, embodiments, geometries, materials, dimensions, ratios, steps, etc., discussed above are illustrative and not essential. Therefore, the scope of the invention should be considered in accordance with the following claims and should be understood as not being limited to the details of the structures and operations shown and described in the specification and drawings.

Claims

1. An apparatus for interacting with one or more digital whole-slice images (WSI) acquired by an imaging device, the apparatus comprising: (a) Display; (b) Memory configured to store computer-executable instructions; and (c) One or more hardware processors communicating with a display and memory, wherein the one or more hardware processors are configured to use computer-executable instructions from memory to drive the display, such that the one or more hardware processors are configured to: Generate a user interface, the user interface comprising an image layer and one or more mask layers covering the image layer, the one or more mask layers having a predetermined opacity level, and The predetermined opacity level is automatically adjusted based on the magnification level of the image layer.

2. The apparatus of claim 1, wherein one or more hardware processors are further configured to adjust a predetermined opacity level in a manner indirectly proportional to the magnification level of the image layer.

3. The apparatus of claim 1 or 2, wherein one or more mask layers include a first mask and a second mask, and one or more hardware processors are further configured to simultaneously adjust the opacity of the first mask and the second mask.

4. The apparatus according to any one of claims 1 to 3, wherein one or more mask layers include a first mask and a second mask, the first mask having a different color relative to the second mask.

5. The device according to claim 4, wherein different colors are selectable by the user.

6. The apparatus according to any one of claims 1 to 5, wherein one or more hardware processors are further configured to: Analyze one or more features of one or more digital WSIs to generate one or more regions of interest within one or more digital WSIs, and One or more mask layers are generated based on one or more regions of interest.

7. The apparatus of claim 6, wherein a predictive artificial intelligence algorithm is used to perform analysis of one or more features of one or more digital WSIs.

8. The apparatus according to any one of claims 1 to 7, wherein one or more hardware processors are further configured to: Generate one or more boundary lines associated with each of the one or more mask layers, and Depending on the magnification level of the image layer, maintain one or more boundary lines with consistent opacity.

9. The apparatus according to any one of claims 1 to 7, wherein one or more hardware processors are further configured to: Generate one or more boundary lines associated with each of the one or more mask layers, and Depending on the magnification level of the image layer, maintain the distinct appearance of one or more boundary lines relative to one or more portions of one or more mask layers.

10. The apparatus according to any one of claims 1 to 7, wherein one or more hardware processors are further configured to: Generate one or more boundary lines associated with each of the one or more mask layers, and Adjust the opacity of one or more boundary lines according to the magnification level of the image layer.

11. The apparatus according to any one of claims 1 to 7, wherein one or more hardware processors are further configured to: Generate one or more boundary lines associated with each of the one or more mask layers, and Adjusting the opacity of one or more boundary lines according to the magnification level of the image layer is different from adjusting the predetermined opacity level of one or more mask layers.

12. The apparatus according to any one of claims 1 to 11, wherein the predetermined opacity level corresponds to the preferred opacity level.

13. The apparatus of claim 12, wherein the preferred opacity level is user-selectable at a 1x magnification level.

14. The apparatus of claim 12, wherein the preferred opacity level is set at the tenant level.

15. The apparatus according to any one of claims 1 to 14, further comprising a network interface, the network interface communicating with a network to receive one or more digital WSIs from an imaging device.

16. A non-transitory computer-readable medium having instructions stored thereon, wherein when the instructions are executed by at least one hardware processor of a system, the system: (a) Acquire one or more digital whole-slice images (WSIs) from an imaging device, the digital WSIs including one or more tissue structures; (b) Identify one or more regions of interest within one or more organizational structures; (c) Generate a graphical user interface, the graphical user interface comprising an image layer and one or more mask layers, the one or more mask layers comprising at least one mask that covers the image layer and corresponds to one or more regions of interest; and (d) Automatically adjust the opacity of the mask according to the zoom level of the image layer.

17. The non-transient computer-readable medium of claim 16, wherein the adjustment of the mask opacity is inversely proportional to the magnification level of the image layer.

18. The non-transient computer-readable medium of claim 16, wherein the adjustment of the mask opacity is performed relative to a preferred opacity level, which is user-selectable.

19. The non-transient computer-readable medium of claim 16, wherein adjusting the opacity of the mask comprises reducing the opacity by 25% relative to a preferred opacity level.

20. A method for presenting one or more digital whole-slice images (WSIs) to a user using a graphical user interface, the method comprising: (a) Receive one or more digital WSIs from the imaging device; (b) Generate a graphical user interface, the graphical user interface comprising an image layer and a mask layer depicting one or more digital WSIs, the mask layer comprising a mask covering the image layer; (c) Set the preferred opacity level corresponding to the mask; (d) Adjust the magnification level of one or more digital WSIs depicted in the image layer; and (e) Automatically adjust the preferred opacity level based on the adjustment of the magnification level of one or more digital WSIs.

Images