The purpose was to develop a fully automatic and accurate tool for prostate and prostate zone segmentation using T2-weighted MRI. Thus, we developed a new neural network named Dense U-Net which was trained on 143 patient datasets and tested on 45 patient datasets. This Dense U-Net compared with the state-of-the-art U-Net achieved an average dice score for the whole prostate of 89.4±0.8% vs. 88.4±0.8%, for the central zone of 83±0.2% vs. 83±0.2%, and for the peripheral zone of 76.9±0.2% vs. 74.6±0.2%, respectively. In conclusion, the developed Dense U-Net was more accurate than the state-of-the-art U-Net for prostate and prostate zone segmentation.
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