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
Unsupervised MR-to-CT Synthesis Using Structure-Constrained CycleGAN
Synthesizing a CT image from an available MR image has recently emerged as a key goal in radiotherapy treatment planning for cancer patients. CycleGANs have achieved promising results on unsupervised MR-to-CT image synthesis; however, because they have no
ieeexplore.ieee.org
=> Completed !
🧑🏻💻 Segmentation Model Training & Liver Datasets Preprocessing🧑🏻💻
Train the TransUNet
preprocess the datasets
=> Completed !
❤️ LG AIMER Lecture ❤️
=> Completed !
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