Prostate cancer (PC) is the most common cancer among men in Western countries. Fortunately, the evolution of PC is typically very slow so the most widely used approach is the imaging follow-up using the multi-parametric prostate magnetic resonance (mp-MRI) examination. The purpose of this work is to develop an automatic U-Net Neural Network (U-NN) to support radiologists in lesion segmentation and prostate zonal segmentation, such as Peripheral Zone (PZ) and Central Gland (CG) on mp-MRI examination.
A U-Net Neural Network-based Approach to Prostate Lesions Segmentation on Multi-parametric Magnetic Resonance Imaging / S. Fouladi, G. Gianini, S. Ibba, M. Cè, M. Cellina, A. Maiocchi, D. Fazzini, S. Papa, M. Alì. ((Intervento presentato al convegno EuSoMII Annual Meeting 2023 AI: Connecting the dots : 13-14 October tenutosi a Pisa nel 2023.
A U-Net Neural Network-based Approach to Prostate Lesions Segmentation on Multi-parametric Magnetic Resonance Imaging
S. Fouladi
;G. Gianini;D. Fazzini;
2023
Abstract
Prostate cancer (PC) is the most common cancer among men in Western countries. Fortunately, the evolution of PC is typically very slow so the most widely used approach is the imaging follow-up using the multi-parametric prostate magnetic resonance (mp-MRI) examination. The purpose of this work is to develop an automatic U-Net Neural Network (U-NN) to support radiologists in lesion segmentation and prostate zonal segmentation, such as Peripheral Zone (PZ) and Central Gland (CG) on mp-MRI examination.
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