G06T7/0016

Cross section views of wounds

A non-transitory computer readable medium storing data and computer implementable instructions that, when executed by at least one processor, cause the at least one processor to perform operations for generating cross section views of a wound, the operations including receiving 3D information of a wound based on information captured using an image sensor associated with an image plane substantially parallel to the wound; generating a cross section view of the wound by analyzing the 3D information; and providing data configured to cause a presentation of the generated cross section view of the wound.

Machine learning systems for generating multi-modal data archetypes

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating multi-modal data archetypes. In one aspect, a method comprises obtaining a plurality of training examples, wherein each training example corresponds to a respective patient and includes multi-modal data, having a plurality of feature dimensions, that characterizes the patient; jointly training an encoder neural network and a decoder neural network on the plurality of training examples; and generating a plurality of multi-modal data archetypes that each correspond to a respective dimension of a latent space, comprising, for each multi-modal data archetype: processing a predefined embedding that represents the corresponding dimension of the latent space using the decoder neural network to generate multi-modal data, having the plurality of feature dimensions, that defines the multi-modal data archetype.

Automated population based assessment of contrast absorption phases

Disclosed are techniques for automated analysis and assessments of contrast medium absorption phases in contrast medium based medical images. A target image set includes a plurality of medical images acquired to image a plurality of contrast medium absorption phases. For the images of the target image set, a set of contrast medium absorption phase probabilities are determined corresponding to likelihoods that a given image corresponds to a given contrast medium absorption phase. The determined sets of contrast medium absorption phases are compared against a reference set of contrast medium absorption phases to determine differences to determine a set of matching scores indicative of how closely the contrast medium absorption phases of the target image set align with the plurality of contrast medium absorption phases as compared to the reference set of contrast medium absorption phases.

Method of evaluating concomitant clinical dementia rating and its future outcome using predicted age difference and program thereof
11751798 · 2023-09-12 · ·

A method of quantitatively evaluating a cognitive status and its future change from a medical image of an individual's brain, the method comprising scanning the individual's brain with a scanning device so as to acquire at least one medical brain image; processing the medical brain image to obtain at least one feature of the image; using a pre-established prediction model to determine a condition of the cognitive status and predict its future change based on the at least one feature obtained.

MEDICAL IMAGE PROCESSING APPARATUS, MEDICAL IMAGE PROCESSING APPARATUS METHOD, AND NON-TRANSITORY, COMPUTER-READABLE MEDIUM

A medical image processing apparatus includes processing circuitry. The processing circuitry obtains a morphological image and a functional image including at least a predetermined anatomical structure of a test subject; obtains reference morphological data and reference functional data corresponding to the morphological image and the functional image, respectively; individually segments the morphological image and the reference morphological data according to a function of interest appearing on the functional image; segments the functional image with reference to the segmental morphological images, and segments the reference functional data with reference to the segmental reference morphological data; performs a first registration process for aligning the segmental morphological images and the segmental reference morphological data with each other; and performs a second registration process for aligning the segmental functional images and the segmental reference functional data with each other according to a result of the first registration process.

Method And Apparatus For Determining Volumetric Data Of A Predetermined Anatomical Feature
20230206448 · 2023-06-29 ·

A method of determining volumetric data of a predetermined anatomical feature is described. The method comprising determining volumetric data of one or more anatomical features present in a field of view of a depth sensing camera apparatus, identifying a predetermined anatomical feature as being present in the field of view of the depth sensing camera apparatus, associating the volumetric data of one of the one or more anatomical features with the identified predetermined anatomical feature, and outputting the volumetric data of the predetermined anatomical feature. An apparatus is also described.

Displaying augmented image data for medically invasive devices via image processing

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.

Augmenting unlabeled images of medically invasive devices via image processing
11663525 · 2023-05-30 ·

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.

Guiding medically invasive devices with radiation absorbing markers via image processing
11657331 · 2023-05-23 ·

A system and method is disclosed for guiding an invasive medical device with radiation absorbing markers. The invasive medical device can include markers with different radiation absorbing properties relative to other portions of the invasive medical device. An imaging device can generate images of the invasive medical device within a patient. A trained model for the invasive medical device can be trained on annotated images of the invasive medical device annotated with marker information identifying the markers and spatial information for the invasive medical device. An imaging computer system can apply the trained model to images of the invasive medical device within the patient including depictions of the markers to determine current spatial information of the invasive medical device inside the patient. The images of the invasive medical device and visual spatial information representing the spatial information of the invasive medical device can be outputted to a display.

RETINAL VASCULAR STRESS TEST FOR DIAGNOSIS OF VISION-IMPAIRING DISEASES

Relationships between morphological changes to an eye due to intraocular pressure changes and blood perfusion and nerve function changes in the retina are determined by colocalizing retinal perfusion data, optic nerve head (ONH) mechanical deformation data, visual field data and nerve fiber data. Perfusion and nerve function changes from intraocular pressure (IOP) changes are determined by colocalizing retinal perfusion data with ONH mechanical deformation data, visual field data and nerve fiber data. Optical coherence tomography-angiography (OCT-A) can be used to generate retinal perfusion data, mechanical deformation data for an imaged volume, and nerve fiber data. A three-dimensional model (e.g., connectivity map or connectivity model) of the vasculature and nerve fibers can be generated from the OCT-A imaging data and used to predict changes in blood perfusion and nerve function in various areas of the retina due to IOP-induced mechanical deformations.