Discover all scientific publications including scientific papers, posters and more.
Data processing pipeline and Artificial Intelligence (AI) for autonomous fusion in transperineal prostate biopsies
European Urology, Volume 85, Supplement 1, 2024
Authors: F. Cianflone, B. Maris, V. Alessandro, F. Artoni, F. Montanaro, G. Pettenuzzo, M.A. Cerruto, P. Fiorini, A. Antonelli
The role of prostate segmentation through AI is to automatize fusion biopsies procedures. Real-time segmentation of the prostate could allow prostate tracking during the procedure, compensating both ultrasound (US) probe and patients movements. Here we present a data processing pipeline and AI for autonomous fusion during transperineal prostate biopsies.
Retrospective analysis of the learning curve in perineal robot- assisted prostate biopsy
Prostate. 2024 Jun 2.
Authors Himmelsbach R, Hackländer A, Weishaar M, Morlock J, Schoeb D, Jilg C, Gratzke C, Grabbert M, Sigle A.
DOI: 10.1002/pros.24753
Magnetic resonance imaging‐transrectal ultrasound (MRI‐TRUS)‐fusion biopsy (FBx) of the prostate allows targeted sampling of suspicious lesions within the prostate, identified by multiparametric MRI. Due to its reliable results and feasibility, perineal MRI/TRUS FBx is now the gold standard for prostate cancer (PC) diagnosis. There are various systems for performing FBx on the market, for example, software‐based, semirobotic, or robot‐assisted platform solutions. Their semiauto-mated workflow promises high process quality independent of the surgeon's experience. The aim of this study was to analyze how the surgeon's experience influences the cancer detection rate (CDR) via targeted biopsy (TB) and the procedure's duration in robot‐assisted FBx.