4 papers
Sli2Vol+: Segmenting 3D Medical Images Based on an Object Estimation Guided Correspondence Flow Network
Delin An, Pengfei Gu, Milan Sonka +2
Deep learning (DL) methods have shown remarkable successes in medical image segmentation, often using large amounts of annotated data for model training. However, acquiring a large…
Spectral U-Net: Enhancing Medical Image Segmentation via Spectral Decomposition
Yaopeng Peng, Milan Sonka, Danny Z. Chen
This paper introduces Spectral U-Net, a novel deep learning network based on spectral decomposition, by exploiting Dual Tree Complex Wavelet Transform (DTCWT) for down-sampling and…
PHG-Net: Persistent Homology Guided Medical Image Classification
Yaopeng Peng, Hongxiao Wang, Milan Sonka +1
Modern deep neural networks have achieved great successes in medical image analysis. However, the features captured by convolutional neural networks (CNNs) or Transformers tend to…
U-Net v2: Rethinking the Skip Connections of U-Net for Medical Image Segmentation
Yaopeng Peng, Milan Sonka, Danny Z. Chen
In this paper, we introduce U-Net v2, a new robust and efficient U-Net variant for medical image segmentation. It aims to augment the infusion of semantic information into low-leve…