[2023 동계 모각코] 3일차 (2024. 1. 9.) 계획
2024. 1. 9. 15:06
2024. 1. 9.(Tue.)
팀원 : 장한, 유정훈, 김승우
팀명 : 승우대칭
⚕️ Medical Imaging ⚕️
Read the Adversarial Model paper
SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth
https://arxiv.org/abs/1810.06498
IEEE TMI paper
SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth
A key limitation of deep convolutional neural networks (DCNN) based image segmentation methods is the lack of generalizability. Manually traced training images are typically required when segmenting organs in a new imaging modality or from distinct disease
arxiv.org
🧑🏻💻 Segmentation Model Training & Liver Datasets Preprocessing🧑🏻💻
Train the TransUNet
preprocess the datasets
❤️ LG AIMER Lecture ❤️
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