Merck Sharp + Dohme Corp.

Msd International Gmbh

Dongqing Zhang

Belma Dogdas

Antong Chen

Ilknur Icke

Sarayu Parimal

Approaches for the automatic segmentation of magnetic resonance (MR) images. Machine learning models segment images to identify image features in consecutive frames at different levels of resolution. A neural network block is applied to groups of MR images to produce primary feature maps at two or more levels of resolution. The images in a given group of MR images may correspond to a cycle and have a temporal order. A second RNN block is applied to the primary feature maps to produce two or more output tensors at corresponding levels of resolution. A segmentation block is applied to the two or more output tensors to produce a probability map for the MR images. The first neural network block may be a convolutional neural network (CNN) block. The second neural network block may be a convolutional long short-term (LSTM) block.

Growing community of inventors

Nashville, TN, United States of America

Dongqing Zhang