GENERATING SEGMENTATION MASK DATA FOR MEDICAL IMAGING DATA

原文（中文）

A framework for generating segmentation mask data for first medical imaging data. The framework may include obtaining a first descriptor for a first location in the first medical imaging data, the first descriptor being representative of values of elements of the first medical imaging data located relative to the first location according to a first predefined pattern. Based on an input of the first descriptor to a trained machine learning model, a class label may be determined for each of a plurality of regions of the first medical imaging data, each region having a respective different predetermined location relative to the first location, the class label for each one of the plurality of regions being determined using a respective different one of a plurality of classifiers of the trained machine learning model. The segmentation mask data may be generated for the first medical imaging data based on the class labels determined for the plurality of regions.