Comprehensive Assessment of MRI-based Artificial Intelligence Frameworks Performance in the Detection, Segmentation, and Classification of Prostate Lesions Using Open-Source Databases
Urol Clin North Am. 2024 Feb;51(1):131-161. doi: 10.1016/j.ucl.2023.08.003. Epub 2023 Sep 11.ABSTRACTNumerous MRI-based artificial intelligence (AI) frameworks have been designed for prostate cancer lesion detection, segmentation, and classification via MRI as a result of intrareader and interreader variability that is inherent to traditional interpretation. Open-source data sets have been released with the intention of providing freely available MRIs for the testing of diverse AI frameworks in automated or semiautomated tasks. Here, an in-depth assessment of the performance of MRI-based AI frameworks for detecting, segmenting, and classifying prostate lesions using open-source databases was performed. Among 17 data sets, 12 were specific to prostate cancer detection/classification, with 52 studies meeting the inclusion criteria.PMID:37945098 | DOI:10.1016/j.ucl.2023.08.003
Source: The Urologic Clinics of North America - Category: Urology & Nephrology Authors: Lorenzo Storino Ramacciotti Jacob S Hershenhouse Daniel Mokhtar Divyangi Paralkar Masatomo Kaneko Michael Eppler Karanvir Gill Vasileios Mogoulianitis Vinay Duddalwar Andre L Abreu Inderbir Gill Giovanni E Cacciamani Source Type: research
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