4 citations · 12 across the 22 of their papers we have counts for
23 papers
UniPET: a universal network for high-quality PET image denoising across varied dose reduction factors
Zhiwen Yang, Yang Zhou, Haowei Chen +4
Most existing deep learning-based PET image denoising methods assume a fixed and known dose reduction factor (DRF) for low-dose PET images. However, these methods encounter signifi…
Linking spatial biology and clinical histology via Haiku
Yan Cui, Jacob S. Leiby, Wenhui Lei +6
Integrating molecular, morphological, and clinical data is essential for basic and translational biomedical research, yet systematic frameworks for jointly modeling these modalitie…
A co-evolving agentic AI system for medical imaging analysis
Songhao Li, Jonathan Xu, Tiancheng Bao +11
Agentic AI is rapidly advancing in healthcare and biomedical research. However, in medical image analysis, their performance and adoption remain limited due to the lack of a robust…
Rethinking Boundary Detection in Deep Learning-Based Medical Image Segmentation
Yi Lin, Dong Zhang, Xiao Fang +3
Medical image segmentation is a pivotal task within the realms of medical image analysis and computer vision. While current methods have shown promise in accurately segmenting majo…
Interactive Segmentation and Report Generation for CT Images
Yannian Gu, Wenhui Lei, Hanyu Chen +2
Automated CT report generation plays a crucial role in improving diagnostic accuracy and clinical workflow efficiency. However, existing methods lack interpretability and impede pa…
MFM-DA: Instance-Aware Adaptor and Hierarchical Alignment for Efficient Domain Adaptation in Medical Foundation Models
Jia-Xuan Jiang, Wenhui Lei, Yifeng Wu +5
Medical Foundation Models (MFMs), trained on large-scale datasets, have demonstrated superior performance across various tasks. However, these models still struggle with domain gap…
LesionDiffusion: Towards Text-controlled General Lesion Synthesis
Wenhui Lei, Henrui Tian, Linrui Dai +2
Fully-supervised lesion recognition methods in medical imaging face challenges due to the reliance on large annotated datasets, which are expensive and difficult to collect. To add…
Unifying Multiple Foundation Models for Advanced Computational Pathology
Wenhui Lei, Yusheng Tan, Anqi Li +7
Foundation models have substantially advanced computational pathology by learning transferable visual representations from large histological datasets, yet their performance varies…
A Synthetic Data-Driven Radiology Foundation Model for Pan-tumor Clinical Diagnosis
Wenhui Lei, Hanyu Chen, Zitian Zhang +13
AI-assisted imaging made substantial advances in tumor diagnosis and management. However, a major barrier to developing robust oncology foundation models is the scarcity of large-s…
Unleashing the Potential of Vision-Language Pre-Training for 3D Zero-Shot Lesion Segmentation via Mask-Attribute Alignment
Yankai Jiang, Wenhui Lei, Xiaofan Zhang +1
Recent advancements in medical vision-language pre-training models have driven significant progress in zero-shot disease recognition. However, transferring image-level knowledge to…
Labeled-to-Unlabeled Distribution Alignment for Partially-Supervised Multi-Organ Medical Image Segmentation
Xixi Jiang, Dong Zhang, Xiang Li +3
Partially-supervised multi-organ medical image segmentation aims to develop a unified semantic segmentation model by utilizing multiple partially-labeled datasets, with each datase…
MedIAnomaly: A comparative study of anomaly detection in medical images
Yu Cai, Weiwen Zhang, Hao Chen +1
Anomaly detection (AD) aims at detecting abnormal samples that deviate from the expected normal patterns. Generally, it can be trained merely on normal data, without a requirement…
CT Synthesis with Conditional Diffusion Models for Abdominal Lymph Node Segmentation
Yongrui Yu, Hanyu Chen, Zitian Zhang +8
Despite the significant success achieved by deep learning methods in medical image segmentation, researchers still struggle in the computer-aided diagnosis of abdominal lymph nodes…
Efficient Subclass Segmentation in Medical Images
Linrui Dai, Wenhui Lei, Xiaofan Zhang
As research interests in medical image analysis become increasingly fine-grained, the cost for extensive annotation also rises. One feasible way to reduce the cost is to annotate w…
CDDSA: Contrastive Domain Disentanglement and Style Augmentation for Generalizable Medical Image Segmentation
Ran Gu, Guotai Wang, Jiangshan Lu +8
Generalization to previously unseen images with potential domain shifts and different styles is essential for clinically applicable medical image segmentation, and the ability to d…
Contrastive Semi-supervised Learning for Domain Adaptive Segmentation Across Similar Anatomical Structures
Ran Gu, Jingyang Zhang, Guotai Wang +5
Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance for medical image segmentation, yet need plenty of manual annotations for training. Semi-Supervised…
HMRNet: High and Multi-Resolution Network with Bidirectional Feature Calibration for Brain Structure Segmentation in Radiotherapy
Hao Fu, Guotai Wang, Wenhui Lei +5
Accurate segmentation of Anatomical brain Barriers to Cancer spread (ABCs) plays an important role for automatic delineation of Clinical Target Volume (CTV) of brain tumors in radi…
Contrastive Domain Disentanglement for Generalizable Medical Image Segmentation
Ran Gu, Jiangshan Lu, Jingyang Zhang +4
Efficiently utilizing discriminative features is crucial for convolutional neural networks to achieve remarkable performance in medical image segmentation and is also important for…
One-shot Weakly-Supervised Segmentation in Medical Images
Wenhui Lei, Qi Su, Ran Gu +5
Deep neural networks usually require accurate and a large number of annotations to achieve outstanding performance in medical image segmentation. One-shot segmentation and weakly-s…
Domain Composition and Attention for Unseen-Domain Generalizable Medical Image Segmentation
Ran Gu, Jingyang Zhang, Rui Huang +3
Domain generalizable model is attracting increasing attention in medical image analysis since data is commonly acquired from different institutes with various imaging protocols and…
Automatic Segmentation of Organs-at-Risk from Head-and-Neck CT using Separable Convolutional Neural Network with Hard-Region-Weighted Loss
Wenhui Lei, Haochen Mei, Zhengwentai Sun +7
Nasopharyngeal Carcinoma (NPC) is a leading form of Head-and-Neck (HAN) cancer in the Arctic, China, Southeast Asia, and the Middle East/North Africa. Accurate segmentation of Orga…
Automatic Segmentation of Gross Target Volume of Nasopharynx Cancer using Ensemble of Multiscale Deep Neural Networks with Spatial Attention
Haochen Mei, Wenhui Lei, Ran Gu +4
Radiotherapy is the main treatment modality for nasopharynx cancer. Delineation of Gross Target Volume (GTV) from medical images such as CT and MRI images is a prerequisite for rad…
Contrastive Learning of Relative Position Regression for One-Shot Object Localization in 3D Medical Images
Wenhui Lei, Wei Xu, Ran Gu +3
Deep learning networks have shown promising performance for accurate object localization in medial images, but require large amount of annotated data for supervised training, which…