Algorithms applied to spatially registered multi-parametric MRI for prostate tumor volume measurement.

ABSTRACT:

Background

Prostate tumor volume correlates with critical components of cancer staging such as Gleason score (GS) grade, predicted disease progression, and metastasis. Therefore, non-invasive tumor volume measurement may elevate clinical management. Radiology assessments of multi-parametric MRI (MP-MRI) commonly visually examine individual images to determine possible tumor presence. This study combines registered MP-MRI into a single image that display normal tissue and possible lesions. This study tests and exploits the vector nature of spatially registered MP-MRI by using supervised target detection algorithms (STDA) and color display and psychovisual analysis (CIELAB) to non-invasively estimate prostate tumor volume.

Methods

MRI, including T1, T2, diffusion [apparent dif

SUBMITTER: Mayer R 

PROVIDER: S-EPMC7719922 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature