2 citations · 3 across the 4 of their papers we have counts for
4 papers
No More Sliding Window: Efficient 3D Medical Image Segmentation with Differentiable Top-k Patch Sampling
Young Seok Jeon, Hongfei Yang, Huazhu Fu +1
3D models surpass 2D models in CT/MRI segmentation by effectively capturing inter-slice relationships. However, the added depth dimension substantially increases memory consumption…
Teaching AI the Anatomy Behind the Scan: Addressing Anatomical Flaws in Medical Image Segmentation with Learnable Prior
Young Seok Jeon, Hongfei Yang, Huazhu Fu +1
Imposing key anatomical features, such as the number of organs, their shapes and relative positions, is crucial for building a robust multi-organ segmentation model. Current attemp…
FCSN: Global Context Aware Segmentation by Learning the Fourier Coefficients of Objects in Medical Images
Young Seok Jeon, Hongfei Yang, Mengling Feng
The encoder-decoder model is a commonly used Deep Neural Network (DNN) model for medical image segmentation. Conventional encoder-decoder models make pixel-wise predictions focusin…
Total Variation and Tight Frame Image Segmentation with Intensity Inhomogeneity
Raymond Chan, Hongfei Yang, Tieyong Zeng
Image segmentation is an important task in the domain of computer vision and medical imaging. In natural and medical images, intensity inhomogeneity, i.e. the varying image intensi…