GROUP_STUDY
2024. 1. 30.(Tue.) 팀원 : 장한, 유정훈, 김승우 팀명 : 승우대칭 ⚕️ Medical Imaging ⚕️ Read the paper Diffusion models in medical imaging: A comprehensive survey https://www.sciencedirect.com/science/article/pii/S1361841523001068 Diffusion models in medical imaging: A comprehensive survey Denoising diffusion models, a class of generative models, have garnered immense interest lately in various deep-learning probl..
2024. 1. 30.(Tue.) 팀원 : 장한, 유정훈, 김승우 팀명 : 승우대칭 ⚕️ Medical Imaging ⚕️ Read the paper Diffusion models in medical imaging: A comprehensive survey https://www.sciencedirect.com/science/article/pii/S1361841523001068 Diffusion models in medical imaging: A comprehensive survey Denoising diffusion models, a class of generative models, have garnered immense interest lately in various deep-learning probl..
2024. 1. 23.(Tue.) 팀원 : 장한, 유정훈, 김승우 팀명 : 승우대칭 ⚕️ Medical Imaging ⚕️ Read the paper A large public dataset of annotated clinical MRIs and metadata of patients with acute stroke https://www.nature.com/articles/s41597-023-02457-9 Nautre paper => Completed ! 🧑🏻💻 Medical Datasets Preprocessing🧑🏻💻 Prep. the Abdomen Dataset from Korea Univ. Hospital Datasets Prep. CHAOS Public Datasets => Completed ..
2024. 1. 23.(Tue.) 팀원 : 장한, 유정훈, 김승우 팀명 : 승우대칭 ⚕️ Medical Imaging ⚕️ Read the paper A large public dataset of annotated clinical MRIs and metadata of patients with acute stroke https://www.nature.com/articles/s41597-023-02457-9 Nautre paper 🧑🏻💻 Medical Datasets Preprocessing🧑🏻💻 Prep. the Abdomen Dataset from Korea Univ. Hospital Datasets Prep. CHAOS Public Datasets ❤️ LG AIMER Lecture ❤️ https..
2024. 1. 17.(Tue.) 팀원 : 장한, 유정훈, 김승우 팀명 : 승우대칭 ⚕️ Medical Imaging ⚕️ Read the paper Deep learning based synthesis of MRI, CT and PET: Review and analysis https://www.sciencedirect.com/science/article/pii/S1361841523003067 Medical Image Analysis paper Deep learning based synthesis of MRI, CT and PET: Review and analysis Medical image synthesis represents a critical area of research in clinical de..
2024. 1. 17.(Wed.) 팀원 : 장한, 유정훈, 김승우 팀명 : 승우대칭 ⚕️ Medical Imaging ⚕️ Read the paper Deep learning based synthesis of MRI, CT and PET: Review and analysis https://www.sciencedirect.com/science/article/pii/S1361841523003067 Medical Image Analysis paper Deep learning based synthesis of MRI, CT and PET: Review and analysis Medical image synthesis represents a critical area of research in clinical de..
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 treatm..
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 lac..
2024. 1. 2.(Tue.) 팀원 : 장한, 유정훈, 김승우 팀명 : 승우대칭 ⚕️ Medical Imaging ⚕️ Read the Adversarial Model paper Unsupervised MR-to-CT Synthesis Using Structure-Constrained CycleGAN https://ieeexplore.ieee.org/document/9164889 IEEE 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 t..
