Segmentation
1 MONAI Segmentation
Lecture
MONAI Segmentation (Video) [20:40]
Reference
2 深度學習與醫學影像分割
影像分割 (Image segmentation) 是一種藉由標記像素點的方式，來找出影像中重要的區域 (例如器官或是腫瘤) 的方法。影像分割可以使原始的影像更容易理解或是分析，有許多的應用。
在這個系列的影片中我們將介紹如何把深度學習應用在影像分割的問題上，並且提供一個實際的範例來演示如何訓練一個醫學影像分割的模型。
Speaker｜王柏川
國立臺灣大學・MeDA Lab
Lecture |
Hands-on |
nnU-Net: The Paradigm of Medical Images Segmentation (Hands-on, for internal use only) [47:10]
3 References
Segmentation Models
Survey: Wang, Risheng, et al. "Medical image segmentation using deep learning: A survey." IET Image Processing (2022).
nnU-Net: Isensee, Fabian, et al. "nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation." Nature methods 18.2 (2021): 203-211.
UNETR: Hatamizadeh, Ali, et al. "UNETR: Transformers for 3D medical image segmentation." Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. 2022.
DiNTS: He, Yufan, et al. "DiNTS: Differentiable neural network topology search for 3d medical image segmentation." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2021.
Segmentation Performance Evaluation
"Towards a guideline for evaluation metrics in medical image segmentation", Müller et al. BMC Research Notes (2022) 15:210 (https://doi.org/10.1186/s13104-022-06096-y)