Abstract: An apparatus for rendering a three-dimensional (3D) polygon mesh includes a processor, and a memory storing instructions, wherein the processor is configured to execute the instructions to obtain a plurality of multi-view images corresponding to a plurality of captured images obtained by capturing an object at different capture camera positions, obtain a 3D polygon mesh for the object, select one or more of the plurality of multi-view images as one or more texture images based on a render camera position and capture camera positions of the plurality of multi-view images, and render the 3D polygon mesh as a two-dimensional (2D) image based on the selected one or more texture images.

Abstract: Systems, computer-implemented methods, and computer program products that can facilitate a transformation of a model of an entity by a model of a plurality of entities are provided. According to an embodiment, a computer-implemented method can comprise identifying a plurality of parameters of a model of a plurality of entities; generating a model of an entity based on collected data of an operation of the entity, wherein the model of the entity comprises a subset of the plurality of parameters; and transforming the model of the entity based the model of the plurality of entities such that a first result from the model of the plurality of entities and a second result from the model of the entity have a relationship that satisfies a defined criterion, given same values used for the subset of the plurality of parameters.

Abstract: A medical imaging apparatus includes processing circuitry configured to acquire a volumetric data set, acquire location information for a layer that is part of a structure represented in the volumetric data set, and perform a ray casting algorithm to generate a rendered image from the volumetric data set. The ray casting algorithm includes, for each of a plurality of rays cast through a volume of the volume of the volumetric data set: determining data values for a plurality of sample positions along the ray; estimating, based on the location information, a position of an intersection point at which the ray intersects the layer; and using a precomputed function to determine a contribution of the intersection point to an aggregated color for the ray.

Abstract: A computer-implemented method for evaluating colonoscopy performance includes: (S1) splitting a video acquired during a colonoscopy examination into a plurality of colonoscopy images; (S2) assigning each of the colonoscopy images into a fold-inspection group or a non-fold-inspection group according to a first classification criterion and a second classification criterion, wherein the first classification criterion comprises at least one of clarity, exposure, level of tissue wrinkling, and level of occlusion in each of the colonoscopy images; and the second classification criterion comprises at least one of an amount of haustrum, an amount of colonic lumen, and a position of the colonic lumen in each of the colonoscopy images; and (S3) determining a performance rating of the colonoscopy examination according to an elapsed time of the fold-inspection group.

Abstract: A neural network based corrector for photon counting detectors is described. A method for photon count correction includes receiving, by a trained artificial neural network (ANN), a detected photon count from a photon counting detector. The detected photon count corresponds to an attenuated energy spectrum. The attenuated energy spectrum is related to characteristics of an imaging object and is based, at least in part, on an incident energy spectrum. The method further includes correcting, by the trained ANN, the detected photon count to produce a corrected photon count. The method may include reconstructing, by image reconstruction circuitry, an image based, at least in part, on the corrected photon count.

Abstract: The disclosure herein provides methods, systems, and devices for virtually staining biological tissue for enhanced visualization without use of an actual dye or tag by detecting how each pixel of an unstained tissue image changes in waveform after staining with a certain dye(s) and/or tag(s) or other transformation under a certain electromagnetic radiation source, developing a virtual staining transform based on such detection, and applying such virtual staining transform to an unstained biological tissue to virtually stain the tissue.

Abstract: A system and method is disclosed for displaying augmented image data for invasive medical devices. A current orientation and a current position of the invasive medical device within a patient can be determined by applying a trained model of the invasive medical device to unannotated images of the invasive medical device as captured by an imaging device. The images of the invasive medical device can be displayed and overlaid with the current orientation and current position of the invasive medical device. User input can be received to initialize tracking of an orientation and a position of the invasive medical device as the invasive medical device is moved within the patient.

Abstract: A lesion detection ensemble machine learning model architecture comprising a plurality of trained machine learning (ML) computer models is provided. A first decoder of a lesion detection ML model processes a medical image input to generate a first lesion mapping prediction. A second decoder of the lesion detection ML model processes the medical image input to generate a second lesion mapping prediction. Combinational logic combines the first and second lesion mapping predictions to generate a combined prediction. Final lesion mapping output logic generates a final lesion prediction based on the combined lesion mapping prediction. The final lesion mapping output logic outputs the final lesion prediction for further downstream computing operations. The first decoder is trained with a first loss function that is configured to counterbalance a training of the second decoder that is trained using a second loss function different from the first loss function.

Abstract: Disclosed is a computer-implemented method of determining an assignment of an object acquire patient image data of interest recognizable in a digital medical patient image such as a tumour or other medical anomaly such as an implant to an anatomical region. The medical patient image is registered with atlas data, The assignment is then determined by calculating a score value defining an amount of volume intersection between the object of interest and a digital object defining a specific anatomic region, for example a bounding box around a specific organ, which is defined in the atlas data.

Abstract: An x-ray image orientation detection and correction system including a detection and correction computing device is provided. The processor of the computing device is programmed to execute a neural network model that is trained with training x-ray images as inputs and observed x-ray images as outputs. The observed x-ray images are the training x-ray images adjusted to have a reference orientation. The processor is further programmed to receive an unclassified x-ray image, analyze the unclassified x-ray image using the neural network model, and assign an orientation class to the unclassified x-ray image. If the assigned orientation class is not the reference orientation, the processor is programmed to adjust an orientation of the unclassified x-ray image using the neural network model, and output a corrected x-ray image. If the assigned orientation class is the reference orientation, the processor is programmed to output the unclassified x-ray image.

Abstract: Solutions for more efficient and effective optical character recognition with respect to an input text segment are disclosed. In one example, a method includes processing an input text image using a deep character overlap detection machine learning model in order to generate a character map for the input text image, an overlap map for the input text image, and an affinity map for the input text image; generating an overlap-aware word boundary recognition output based at least in part on the character map, the overlap map, and the affinity map, wherein the overlap-aware word boundary recognition output describes one or more inferred word regions of the input text image; and performing one or more prediction-based actions based at least in part on the overlap-aware word boundary recognition output.

Abstract: A computer implemented method of generating at least one shape of a region of interest in a digital image is provided.

Abstract: Methods and systems are presented to analyze a retinal image of an eye and assigns features to known anatomical structures such as retinal layers. One example method includes receiving interferometric image data of an eye. A set of features is identified in the image data. A first subset of identified features is associated with known retinal structures using prior knowledge. A first set of characteristic metrics is determined of the first subset of features. A second set of characteristic metrics is determined of a second subset of features. Using the characteristic metrics of the first and the second sets, the second subset of features is associated with the retinal structures. Another example method includes dividing interferometric image data into patches. The image data in each patch is segmented to identify one or more layer boundaries. The segmentation results from each patch are stitched together into a single segmentation dataset.

Abstract: A system and method is disclosed for augmenting image data of an invasive medical device using optical imaging. An optical imaging sensor, separate from the invasive medical device, can generate images of the medical device within a patient. A trained model for the invasive medical device can be trained on annotated images of the invasive medical device with orientation and distance information of the invasive medical device. An imaging computer system can apply the trained model to images of the invasive medical device within the patient to determine a current orientation and a current distance of the invasive medical device. The images of the invasive medical device as captured by the optical imaging sensor, visual orientation information representing the current orientation of the invasive medical device, and visual distance information representing the current distance of the invasive medical device within the patient can be displayed.

Abstract: Systems and methods for automated assessment of a vessel are provided. One or more input medical images of a vessel of a patient are received. A plurality of vessel assessment tasks for assessing the vessel is performed using a machine learning based model trained using multi-task learning. The plurality of vessel assessment tasks are performed by the machine learning based model based on shared features extracted from the one or more input medical images. Results of the plurality of vessel assessment tasks or a combination of the results of the plurality of vessel assessment tasks are output.

Abstract: An image diagnosis assisting apparatus according to the present invention executes: processing of inputting an image of a tissue or cell; processing of extracting a feature amount of a tissue or cell from a processing target image; processing of extracting a feature amount of a tissue or cell from an image having a component different from that of the target image; and processing of determining presence or absence of a lesion and lesion probability for each of the target images by using a plurality of the feature amounts.

Abstract: An automated segmentation system for medical imaging data segments data into muscle and fat volumes, and separates muscle volumes into discrete muscle group volumes using a plurality of models of the medical imaging data, and wherein the medical imaging data includes data from a plurality of imaging modalities.

Abstract: Methods and systems are provided for synchronizing image capture at a multi-detector imaging system. In one example, a method includes coordinating cycling of each microscope assembly of the multi-detector imaging system through a selection of illumination channels, each microscope assembly configured to obtain an image of a portion of one of more than one microplate wells simultaneously, to generate complete images of the more than one microplate wells concurrently.

Abstract: Embodiments provide slide navigation technology that addresses challenges in digital pathology of navigating and viewing high resolution slide images. Example systems comprise a virtual slide stage (VSS) having at least one sensor that detects user movement of a target placed on the VSS, and an input component, coupled to the VSS, which provides quick function movement control of the target via quick functions. The systems also comprise a connector component that connects the VSS to a user device and transmits output from the at least one sensor and input component to the user device. The systems further comprise a computer processor, in communication with the VSS, which processes the output using a computational model to generate data representing movement profiles of the target. The computer processor executes a software component, causing the output, translated based on the movement profiles, to be relayed via a viewing application on the user device.

Abstract: A method comprises obtaining reference data about a 3D calibration object, the reference data comprising known coordinates for a plurality of points on the object, and obtaining measurement data comprising measurements for the plurality of points on the object, the measurement data having been generated based on scanning of the object by an uncalibrated intraoral scanner. The method comprises comparing the measurement data to the reference data to determine differences therebetween and applying the determined differences between the measurement data and the reference data for the plurality of points to a function to generate a compensation model that compensates for one or more inaccuracies of the intraoral scanner. The compensation model is then stored, wherein the compensation model causes the intraoral scanner to be a calibrated intraoral scanner and is usable to correct measurement errors of the intraoral scanner caused by the one or more inaccuracies of the intraoral scanner.

Abstract: An example system includes a thermal camera, a memory, and processing circuitry coupled to the thermal camera and the memory. The processing circuitry is configured to acquire a core temperature of a patient and acquire a first thermal image associated with the patient. The processing circuitry is configured to determine, based on the first thermal image, a first sensed temperature of a location associated with the patient. The processing circuitry is configured to determine a core temperature delta between the core temperature and the first sensed temperature. The processing circuitry is configured to acquire a second thermal image associated with the patient. The processing circuitry is configured to determine, based on the second thermal image, a second sensed temperature. The processing circuitry is configured to determine, based on the second sensed temperature and the core temperature delta, a measure of the core temperature.

Abstract: A label generating system operates to generate an artificial intelligence model by: training on a training data set that includes the plurality of medical scans with the corresponding global labels; generating testing global probability data by performing an inference function that utilizes the artificial intelligence model on the plurality of medical scans with the corresponding global labels, wherein the testing global probability data indicates a testing set of global probability values corresponding to the set of abnormality classes, and wherein each of the testing set of global probability values indicates a probability that a corresponding one of the set of abnormality classes is present in each of the plurality of medical scans with the corresponding global labels; comparing the testing set of global probability values to a corresponding confidence threshold for each of the plurality of medical scans selected based on the corresponding one of the global labels; generating an updated training data set b

Abstract: An apparatus for classifying a contrast level of an image is provided. One or more processors execute instructions stored in one or more memory devices which configure the one or more processors to obtain an image from an image source, extract intensity values for each pixel of the obtained image, calculate a probability distribution for the obtained image representing a number of pixels at each unique pixel value, determine, from the calculated probability distribution, a spread value representing a series pixel values including at least a predetermined number of pixels at each pixel value in the series of pixel values and classify the obtained image a member of one of three classes based on the calculated probability distribution and the determined spread value.

Abstract: Some embodiments of the disclosure provide an artificial neural network system for recognizing a lesion in a fundus image. The system includes a pre-processing module configured to pre-process a target fundus image and a reference fundus image taken from one person separately, a first neural network (12) configured to generate a first advanced feature set from the target fundus image, a second neural network (22) configured to generate a second advanced feature set from the reference fundus image, a feature combination module (13) configured to combine the first advanced feature set and the second advanced feature set to form a feature combination set, and a third neural network (14) configured to generate, according to the feature combination set, a judgmental result of lesions.

Abstract: There is provided a system for computing connectivity of medical imaging network nodes, comprising: at least one hardware processor executing a code for: monitoring packets transmitted over a network connecting a plurality of network nodes, analyzing the monitored packets to identify packets associated with a Digital Imaging and Communications in Medicine (DICOM) protocol, analyzing the packets associated with the DICOM protocol to identify medical imaging network nodes implementing the DICOM protocol, designating a respective medical imaging type for each node of the medical imaging network nodes, and computing a data structure storing connectivity of the medical imaging network nodes each designated with the respective medical imaging type.

Abstract: An apparatus for assessing a patient's vasculature and a corresponding method identify the bifurcations in a vessel of interest on the basis of a local change in at least one geometric parameter value of the vessel of interest and adjust the fluid dynamics inside the vessel of interest to take account for said bifurcations.

Abstract: Disclosed is a method, a computer readable storage medium and an apparatus for processing medical image data. Input medical image data is received at a data processing system, which is an artificial intelligence-based system. An identification process is performed at the data processing system on the input medical image data to identify a volume of interest within which an instance of a predetermined anatomical structure is located. First and second determination processes are performed at the data processing system to determine, respectively, first and second anatomical directions for the instance of the anatomical structure that are defined relative to the coordinate system of the input medical image data. Output data relating to the first and second anatomical directions is output from the data processing system.

Abstract: Methods for measuring and verifying drug portions while avoiding the need to teach verification devices is provided. Characteristic key data of a drug type are compiled with a calibrated camera of a measuring device, stored in a storage device, and retrieved from or transmitted to a verification device. Individual key data for a drug portion to be verified are compiled using a calibrated camera of the verification device and compared with the characteristic key data. A digital image of a drug portion to be verified is generated with a calibrated camera and transferred to a control unit. The control unit determines individual key data for the drug portion to be verified using known calibration parameters of the camera and the digital image, compares the individual key data with characteristic key data of the corresponding drug type and verifies or rejects the drug portion based on the results of the comparison. Systems and computer readable medium are also provided.

Abstract: A system and method for managing sensors including determining health operation states of the sensors correlative with sensor accuracy, classifying the sensors by their respective health operation state, and teaming two sensors each having a health operation state that is intermediate to give a team having a health operation state that is healthy. The sampling frequency of the sensors to determine sensor accuracy may be dynamic.

Abstract: A system and method for displaying and navigating breast tissue is configured for or includes obtaining a plurality of 2D and/or 3D images of a patient's breast; generating a synthesized 2D image of the breast from the obtained images; displaying the synthesized 2D image; receiving a user command, or otherwise detecting through a user interface, a user selection or other indication of an object or region in the synthesized 2D image; and displaying at least a portion of one or more images from the plurality, including a source image and/or most similar representation of the user selected or indicated object or region.

Abstract: A system and method for augmenting unlabeled imaging data of invasive medical devices is disclosed. An imaging device can generate images of the invasive medical device inside a patient. A trained model for the invasive medical device can be trained on annotated images of the invasive medical device having labels indicating orientation and position information. An imaging computer system can apply the trained model to unlabeled images of the invasive medical device within the patient to determine a current orientation and a current position of the invasive medical device inside the patient. The images of the invasive medical device, visual orientation information representing the current orientation of the invasive medical device, and visual position information representing the current position of the invasive medical device inside the patient can be outputted to a display.

Abstract: An esophageal monitoring device includes a camera and, optionally, one or more lights to enable visualization of an interior of a subject's esophagus. Visualization of the interior of the subject's esophagus before and after a left atrial ablation procedure may enable a healthcare provider to determine whether or not the left atrial ablation procedure has damaged the subject's esophagus before the subject experiences any symptoms of such damage. An esophageal monitoring device may also include sensors and/or markers that enable a determination of its location within a subject's esophagus. Such an esophageal monitoring device may be configured for three-dimensional mapping, and enable the generation of an accurate three-dimensional map of the physical relationship between a subject's esophagus and the left atrium of his or her heart. Methods of monitoring a subject's esophagus while a left atrial ablation procedure is being conducted on the subject's heart are also disclosed.

Abstract: Seismic image processing including filtering a three-dimensional (3D) seismic image for random noise attenuation via multiple processors. The filtering includes receiving a 3D image cube of seismic image data, decomposing the 3D image cube into 3D sub-cubes for parallel computation on the multiple processors, designing and applying a two-dimensional (2D) adaptive filter for image points on 2D image slices of the 3D sub-cubes via the multiple processors to give filtered 3D sub-cubes, and summing the filtered 3D sub-cubes to give a filtered 3D image cube.

Abstract: Systems and methods are provided to aid in planning at least a portion of a total knee arthroplasty procedure. The system and method automatically aligns the implant components and the bones according to a desired clinical alignment goal with minimum user input. The system and method further allows the user to adjust the position and orientation of the femur, tibia, or implant in a clinical direction regardless of a pre-adjusted position and orientation of the femur, tibia, or implant. The graphical user interface is provided that includes a three-dimensional (3-D) view window, a view options window, a patient information window, an implant family window, a workflow-specific tasks window, and a limb and knee alignment measures window.

Abstract: To provide a medical image processing apparatus and a medical image processing method enabling a reduction in burden of re-imaging and re-interpretation of a medical image. The medical image processing apparatus for processing a medical image includes: a detection section that detects, from the medical image, a candidate region which is a region including a lesion candidate or target tissue, and that calculates an identification score for the candidate region; a designated region acquisition section that acquires a designated region which is a region designated by an operator; and a redetection section that calculates an identification score for the designated region based on the designated region and multiple predefined regions which are regions used in a process of detecting the candidate region.

Abstract: An ultrasonic diagnosis apparatus includes a position detector, and control circuitry. The position detector detects a position in a three-dimensional space of one of an ultrasonic image and an ultrasonic probe. The control circuitry uses a vivisection view defined in a three-dimensional space. The control circuitry associates a structure related to a subject included in the ultrasonic image with a structure included in the vivisection view using a position and orientation in a first three-dimensional coordinate system of the structure related to the subject included in the ultrasonic image and a position and orientation in a second three-dimensional coordinate system of the structure included in the vivisection view.

Abstract: An image coding method includes selecting two or more transform components from among a plurality of transform components that include a translation component and non-translation components, the two or more transform components serving as reference information that represents a reference destination of a current block; coding selection information that identifies the two or more transform components that have been selected from among the plurality of transform components; and coding the reference information of the current block by using reference information of a coded block different from the current block.

Abstract: An optical measuring device includes at least one optical sensor configured for optical capture of at least one measurement object at multiple image recording positions. The optical measuring device includes at least one display device configured to display, for multiple predetermined and/or determinable image recording positions, in each case a schematic representation of an image to be recorded at the respective image recording position. The optical measuring device includes at least one data processing unit and at least one interface. The interface is configured to provide at least one item of manipulation information to the data processing unit. The data processing unit is configured to, based on the manipulation information, adapt at least one of the image recording position and an image recording parameter of at least one of the images to be recorded.

Abstract: Medical image based collaboration system and methods are provided. A collaboration server 40 creates a medical image based case in response to a request from a requesting system 10 and populates the case with the minimum required information comprising at least a digital medical image and a case number. The collaboration server 40 provides the medical image based case to a consulting system 30 and receives analysis information in response. The collaboration server 40 stores the analysis information in association with the medical image based case and provides the analysis information to the consulting system 30 to complete the medical image based collaboration.

Abstract: Methods and systems for determining a drop delay of a flow stream in a flow cytometer are provided. Aspects of the methods according to certain embodiments include capturing an image of the flow stream to obtain an imaged flow stream, identifying a disturbance at a break off point in the imaged flow stream and calculating the drop delay of the flow stream based on the identified disturbance. Systems for practicing the subject methods having an imaging sensor for capturing one or more images of the flow stream and a processor configured to identify a disturbance at a break off in the imaged flow stream and calculating the drop delay using the imaged flow stream are also provided. Non-transitory computer readable storage mediums are also described.

Abstract: A method for image segmentation comprises receiving volumetric image data for an anatomical region and generating a first volumetric patch from the volumetric image data. The method also comprises generating a second volumetric patch from the first volumetric patch by weighting a plurality of volumetric units in the first volumetric patch and receiving the second volumetric patch as an input to a convolutional neural network. The method also comprises conducting a down-sampling filter process and conducting an up-sampling filter process within the convolutional neural network.

Abstract: Disclosed is a stereo matching method of images performed by a system implemented by a computer, including the steps of: receiving a pair of images obtained at different time points; generating a feature map by extracting features of each pixel of the pair of images; generating sequentially cost volumes for partial time points based on the feature map and generating a feature map for the entire disparity by fusing the cost volumes using 2D convolution; and generating a final disparity map by refining the generated feature map.

Abstract: The present disclosure provides a system comprising a SPECT or PET device; a CT device; and a computer comprising memory and a processor in communication with the memory, the memory comprising a computer application program for a method of performing dosimetric analysis of an organ. The computer application program is executable by the processor to perform the method. The method comprising receiving single photon emission computed tomography (SPECT) or positron emission tomography (PET) images at time instances, the SPECT or PET images relating to the organ. The method then receives a computed tomography (CT) image at one of the time instances, the CT image relating to the organ. Virtual CT images are then generated at the other time instances based on the received SPECT or PET images and the CT image. An absorbed dose of ionising radiation on the organ can then be measured based on the received SPECT or PET images, the received CT image, and the generated virtual CT images.

Abstract: An image generation system is provided to: receive a 3D CAD (computer aided design) model comprising 3D model images of a target object; generate a graph data structure; based on the 3D CAD model of the target object and the graph data structure, generate a plurality of augmented CAD models of the target object comprising a plurality of data sets, each data set respectively corresponding to an associated one of a plurality of attribute classes, each data set comprising a plurality of 2D model images; input the plurality of data sets into a generative adversarial network; generate synthetic photorealistic images of the target object using the plurality of generators of the generative adversarial network, the synthetic photorealistic images including attributes in accordance with the plurality of data sets corresponding to the plurality of attribute classes; and output the synthetic photorealistic images of the target object.

Abstract: A system and method for providing online games on client devices based on capabilities of the client devices are disclosed. Device capability information may be obtained from the client devices during the online game. Values of one or more capability parameters may be determined based on the device capability information obtained. Device profiles may be assigned to the client devices based on the determined values of the capability parameters. One or more game features may be adjusted in accordance with the assigned device profile for implementing the online game on the client devices. The adjustable game features may include frame rate, level of detail of rendering, level of 3D graphics, level of collision effects, animation type, gameplay available for user interaction, gameplay content for user interaction, communication mode, physics effects available for display, level of artificial intelligence, and/or any other features of the online game.

Abstract: The present disclosure relates to systems and methods for magnetic resonance imaging. The method may include obtaining primary imaging data associated with a region of interest (ROI) of a subject and obtaining secondary data associated with the ROI. The method may also include determining secondary imaging data based on the secondary data by using a trained model. The method may further include reconstructing a magnetic resonance image based on the primary imaging data and the secondary imaging data.

Abstract: A liver fibrosis recognition method based on medical images and a computing device using thereof obtains a plurality of first binary images by segmenting a region of interest in each of a plurality of medical images of a liver. A rectangular region is created for each first binary image, and a plurality of second binary images is obtained by generating a second binary according to each rectangular region and the first binary image. A feature map is obtained from each liver medical image and images are generated according to the second binary images and corresponding to the plurality of feature maps. A model for recognition is iteratively trained based on the plurality of final images and recognition of liver fibrosis in patients is then achievable using the model.

Abstract: A system may include an ultrasound probe and a controller unit configured to obtain a baseline ultrasound image of a patient's breast area using the ultrasound probe and to obtain a follow-up ultrasound image of the patient's breast area using the ultrasound probe. The controller unit may further be configured to use one or more machine learning models to compare the baseline ultrasound image with the follow-up ultrasound image; detect a change in a morphology or integrity of the patient's breast area based on the comparison of the baseline ultrasound image with the follow-up ultrasound image; and generate a recommendation for a medical intervention based on the detected change.

Abstract: A system determines which user of multiple users provided input through a single input device. A mechanism captures images of the one or more users. When input is detected, the images may be processed to determine which user provided an input using the input device. The images may be processed to identify each users head and eyes, and determine the focus point for each user's eyes. The user which has eyes focused at the input location is identified as providing the input. When the input mechanism is a touch screen, the user having eyes focused on the touch screen portion which was touched is identified as the source of the input.

Abstract: Aspects of the invention include generating a cryptographic key to restrict access to a resource. The cryptographic key being defined by a key token. An exemplary method includes designating a storage field in metadata of the key token, in metadata of a cryptographic key data set record that includes the key token, or in a resource access control database that controls use of the cryptographic key for inclusion of an indicator that the cryptographic key may or may not be deleted or modified. The indicator in the designated storage field is set to indicate whether or not the cryptographic key may be deleted or modified.