Rensselaer Polytechnic Institute

Hengtao Guo

Pingkun Yan

Xinrui Song

Xuanang Xu

A method of multi-modal image registration is provided. The method includes receiving as input a fixed image from a first imaging device, receiving as input a moving image from a second imaging device, performing feature extraction on the fixed image via a first feature extractor to generate a fixed image feature map, performing feature extraction on the moving image via second feature extractor to generate a moving image feature map, performing cross-modal attention on the fixed image feature map and the moving image feature map to generate cross-modal feature attention data, performing deep registration on the cross-modal feature attention data via a deep registrator, and outputting a multi-modal registered image.

Systems and methods for multi-modal multi-dimensional image registration

A method of ultrasound image volume reconstruction includes: providing a convolutional neural network ('CNN'); receiving a first dataset comprising at least one pair of consecutive ultrasound images; inputting the first dataset to the CNN; training the CNN with the first dataset; receiving a second dataset comprising an ultrasound video comprising a plurality of consecutive ultrasound images; inputting the second dataset to the CNN; and processing, by the CNN, the second dataset to produce as output a reconstructed 3D ultrasound image volume.

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Troy, NY, United States of America

Hengtao Guo