2 citations · 2 across the 10 of their papers we have counts for
4 papers · 1 filter
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…
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…
Self Pre-training with Topology- and Spatiality-aware Masked Autoencoders for 3D Medical Image Segmentation
Pengfei Gu, Huimin Li, Yejia Zhang +2
Masked Autoencoders (MAEs) have been shown to be effective in pre-training Vision Transformers (ViTs) for natural and medical image analysis problems. By reconstructing missing pix…
Densely Decoded Networks with Adaptive Deep Supervision for Medical Image Segmentation
Suraj Mishra, Danny Z. Chen
Medical image segmentation using deep neural networks has been highly successful. However, the effectiveness of these networks is often limited by inadequate dense prediction and i…