Automatic segmentation of prostate zonal anatomy on MRI: a systematic review of the literature.

ABSTRACT:

Objectives

Accurate zonal segmentation of prostate boundaries on MRI is a critical prerequisite for automated prostate cancer detection based on PI-RADS. Many articles have been published describing deep learning methods offering great promise for fast and accurate segmentation of prostate zonal anatomy. The objective of this review was to provide a detailed analysis and comparison of applicability and efficiency of the published methods for automatic segmentation of prostate zonal anatomy by systematically reviewing the current literature.

Methods

A Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) was conducted until June 30, 2021, using PubMed, ScienceDirect, Web of Science and EMBase databases. Risk of bias and applicability based on Quality Ass

SUBMITTER: Wu C 

PROVIDER: S-EPMC9772373 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature