Medical College of Wisconsin
CTSICores SearchResearch InformaticsREDCap

Homologous point transformer for multi-modality prostate image registration. PeerJ Comput Sci 2022;8:e1155



Pubmed ID


Pubmed Central ID





Registration is the process of transforming images so they are aligned in the same coordinate space. In the medical field, image registration is often used to align multi-modal or multi-parametric images of the same organ. A uniquely challenging subset of medical image registration is cross-modality registration-the task of aligning images captured with different scanning methodologies. In this study, we present a transformer-based deep learning pipeline for performing cross-modality, radiology-pathology image registration for human prostate samples. While existing solutions for multi-modality prostate image registration focus on the prediction of transform parameters, our pipeline predicts a set of homologous points on the two image modalities. The homologous point registration pipeline achieves better average control point deviation than the current state-of-the-art automatic registration pipeline. It reaches this accuracy without requiring masked MR images which may enable this approach to achieve similar results in other organ systems and for partial tissue samples.

Author List

Ruchti A, Neuwirth A, Lowman AK, Duenweg SR, LaViolette PS, Bukowy JD


Peter LaViolette PhD Professor in the Radiology department at Medical College of Wisconsin