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nnU-Net weights for Prostate segmentation used in PI-CAI Challenge - Phase 1

Year: 2023

Type: dataset

Abstract: nnU-Net weights for Prostate segmentation used in PI-CAI Challenge - Phase 1. A baseline nnU-Net was trained to segment the prostate gland, using the 1500 cases training data from PI-CAI dataset. The network took as input 3 modalities (T2w, ADC, high DWIb), and the ground truth was AI-derived prostate masks. See Abstract "Deep learning for detection and diagnosis of prostate cancer from bpMRI and PSA: Guerbet’s contribution to the PI-CAI 2022 Grand Challenge" for further information.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.7680507

Authors: Debs, Noëlie, Routier, Alexandre, Abi-Nader, Clément, Marcoux, Arnaud, Nicolas, François, Bône, Alexandre, Rohé, Marc-Michel

Institution: Guerbet (France)

Language: English

Topic: Medical Image Segmentation Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W4393472064

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