System and Method for Interpretation of Multiple Medial Images using Deep Learning
개요
발명자
Scott McKinney; Marcin Sieniek; Varun Godbole; Shravya Shetty; Natasha Antropova; Jonathan Godwin; Christopher Kelly; Jeffrey De Fauw
IPC 분류
CPC 분류
A method is disclosed of processing a set of images. Each image in the set has an associated counterpart image, e.g., a contralateral, prior or multimodal image. One or more regions of interest (ROIs) are identified in one or more of the images in the set of images. For ROI identified, a reference region is identified in the associated counterpart image. ROIs and associated reference regions are cropped out, thereby forming cropped pairs of images. The cropped image pairs are fed to a deep learning model trained to make a prediction of probability of a state of the ROI, e.g., disease state, which generates a prediction for each cropped pair. The model generates an overall prediction P from each of the predictions. A visualization of the set of medical images and the associated counterpart images including the cropped pair of images is generated, e.g., on a workstation.
원문 (중국어)
A method is disclosed of processing a set of images. Each image in the set has an associated counterpart image, e.g., a contralateral, prior or multimodal image. One or more regions of interest (ROIs) are identified in one or more of the images in the set of images. For ROI identified, a reference region is identified in the associated counterpart image. ROIs and associated reference regions are cropped out, thereby forming cropped pairs of images. The cropped image pairs are fed to a deep learning model trained to make a prediction of probability of a state of the ROI, e.g., disease state, which generates a prediction for each cropped pair. The model generates an overall prediction P from each of the predictions. A visualization of the set of medical images and the associated counterpart images including the cropped pair of images is generated, e.g., on a workstation.