US Patent Application 17752506. Lesion Detection and Segmentation simplified abstract
Contents
Lesion Detection and Segmentation
Organization Name
International Business Machines Corporation
Inventor(s)
Giovanni John Jacques Palma of Velizy Villacoublay (FR)
Amin Katouzian of Lexington MA (US)
Lesion Detection and Segmentation - A simplified explanation of the abstract
This abstract first appeared for US patent application 17752506 titled 'Lesion Detection and Segmentation
Simplified Explanation
The patent application describes mechanisms for detecting lesions in diffusion weighted imaging (DWI) images.
- The mechanisms receive a set of DWI images of an anatomical structure from a medical imaging computer system.
- The set of DWI images includes multiple images with different b-values.
- The mechanisms generate a second set of DWI images by applying a predetermined criterion to the first set of images.
- The second set of DWI images includes images with different b-values.
- The mechanisms extract feature data from the second set of DWI images.
- The feature data is input into one or more computer neural networks.
- The neural networks process the feature data and generate an output.
- The output can include a classification of the lesion or a mask indicating the presence of a lesion.
Original Abstract Submitted
Mechanisms are provided for detecting lesions in diffusion weighted imaging (DWI) images. The mechanisms receive a first set of DWI images corresponding to a anatomical structure, from medical imaging computer system(s). The first set of DWI images comprises a plurality of DWI images having at least two different b-values. The mechanisms generate a second set of DWI images from the first set of DWI images based on at least one predetermined criterion. The second set of DWI images comprises different DWI images having different b-values. The mechanisms extract feature data from the second set of DWI images, input the feature data into at least one computer neural network, and generate an output from the neural network(s) comprising at least one of a lesion classification or a lesion mask based on results of processing, by the neural network(s), of the feature data extracted from the second set of DWI images.