Development and validation of a framework for registration of whole-mount radical prostatectomy histopathology with three-dimensional transrectal ultrasound.

ABSTRACT:

Purpose

Artificial intelligence (AI) has the potential to improve diagnostic imaging on multiple levels. To develop and validate these AI-assisted modalities a reliable dataset is of utmost importance. The registration of imaging to pathology is an essential step in creating such a dataset. This study presents a comprehensive framework for the registration of 3D transrectal ultrasound (TRUS) to radical prostatectomy specimen (RPS) pathology.

Methods

The study enrolled patients who underwent 3D TRUS and were scheduled for radical prostatectomy. A four-step process for registering RPS to TRUS was used: image segmentation, 3D reconstruction of RPS pathology, registration and ground truth calculation. Accuracy was assessed using a target-registration error (TRE) based on landmar

SUBMITTER: Jager A 

PROVIDER: S-EPMC11966914 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature