27 citations · 38 across the 9 of their papers we have counts for
9 papers
MedFMC: A Real-world Dataset and Benchmark For Foundation Model Adaptation in Medical Image Classification
Dequan Wang, Xiaosong Wang, Lilong Wang +12
Foundation models, often pre-trained with large-scale data, have achieved paramount success in jump-starting various vision and language applications. Recent advances further enabl…
propnet: Propagating 2D Annotation to 3D Segmentation for Gastric Tumors on CT Scans
Zifan Chen, Jiazheng Li, Jie Zhao +5
**Background:** Accurate 3D CT scan segmentation of gastric tumors is pivotal for diagnosis and treatment. The challenges lie in the irregular shapes, blurred boundaries of tumors,…
Region-Aware Metric Learning for Open World Semantic Segmentation via Meta-Channel Aggregation
Hexin Dong, Zifan Chen, Mingze Yuan +5
As one of the most challenging and practical segmentation tasks, open-world semantic segmentation requires the model to segment the anomaly regions in the images and incrementally…
BEFD: Boundary Enhancement and Feature Denoising for Vessel Segmentation
Mo Zhang, Fei Yu, Jie Zhao +2
Blood vessel segmentation is crucial for many diagnostic and research applications. In recent years, CNN-based models have leaded to breakthroughs in the task of segmentation, howe…
PGU-net+: Progressive Growing of U-net+ for Automated Cervical Nuclei Segmentation
Jie Zhao, Lei Dai, Mo Zhang +5
Automated cervical nucleus segmentation based on deep learning can effectively improve the quantitative analysis of cervical cancer. However, accurate nuclei segmentation is still…
Annotation-Free Cardiac Vessel Segmentation via Knowledge Transfer from Retinal Images
Fei Yu, Jie Zhao, Yanjun Gong +6
Segmenting coronary arteries is challenging, as classic unsupervised methods fail to produce satisfactory results and modern supervised learning (deep learning) requires manual ann…
ASCNet: Adaptive-Scale Convolutional Neural Networks for Multi-Scale Feature Learning
Mo Zhang, Jie Zhao, Xiang Li +2
Extracting multi-scale information is key to semantic segmentation. However, the classic convolutional neural networks (CNNs) encounter difficulties in achieving multi-scale inform…
Automated Segmentation of Pulmonary Lobes using Coordination-Guided Deep Neural Networks
Wenjia Wang, Junxuan Chen, Jie Zhao +4
The identification of pulmonary lobes is of great importance in disease diagnosis and treatment. A few lung diseases have regional disorders at lobar level. Thus, an accurate segme…
Automated Segmentation of Cervical Nuclei in Pap Smear Images using Deformable Multi-path Ensemble Model
Jie Zhao, Quanzheng Li, Xiang Li +2
Pap smear testing has been widely used for detecting cervical cancers based on the morphology properties of cell nuclei in microscopic image. An accurate nuclei segmentation could…