47 citations · 50 across the 6 of their papers we have counts for
6 papers
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…
FiAt-Net: Detecting Fibroatheroma Plaque Cap in 3D Intravascular OCT Images
Yaopeng Peng, Zhi Chen, Andreas Wahle +3
The key manifestation of coronary artery disease (CAD) is development of fibroatheromatous plaque, the cap of which may rupture and subsequently lead to coronary artery blocking an…
Boosting Medical Image Classification with Segmentation Foundation Model
Pengfei Gu, Zihan Zhao, Hongxiao Wang +5
The Segment Anything Model (SAM) exhibits impressive capabilities in zero-shot segmentation for natural images. Recently, SAM has gained a great deal of attention for its applicati…
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…
Keep Your Friends Close & Enemies Farther: Debiasing Contrastive Learning with Spatial Priors in 3D Radiology Images
Yejia Zhang, Nishchal Sapkota, Pengfei Gu +3
Understanding of spatial attributes is central to effective 3D radiology image analysis where crop-based learning is the de facto standard. Given an image patch, its core spatial p…