Meeting Banner
Abstract #3748

Prostate DWI co-registration via maximization of hybrid statistical likelihood and cross-correlation for improved ADC and computed ultra-high b-value DWI calculation

Daniel S. Cho 1 , Farzad Khalvati 2 , Alexander Wong 1 , David A Clausi 1 , and Masoom Haider 2

1 Systems Design Engineering, University of Waterloo, Waterloo, Ontario, Canada, 2 University of Toronto, Ontario, Canada

Diffusion weighted imaging (DWI) has gained significant attention for prostate cancer imaging as its derived modalities such as apparent diffusion coefficient and computed high b-value images are commonly employed for prostate cancer analysis. In this work, a novel technique to register a set of DWI acquisitions across multiple b-values was proposed. The proposed registration adapted b-spline registration with a new hybrid similarity metric, which utilized statistical likelihood and cross-correlation. The DWI co-registration showed the improved contrast-to-noise ratio on DWI acquisitions across multiple b-values as well as ADC map.

This abstract and the presentation materials are available to members only; a login is required.

Join Here