35 citations · 61 across the 15 of their papers we have counts for
15 papers
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…
MedDiff-FM: A Diffusion-based Foundation Model for Versatile Medical Image Applications
Yongrui Yu, Yannian Gu, Shaoting Zhang +1
Diffusion models have achieved significant success in both natural image and medical image domains, encompassing a wide range of applications. Previous investigations in medical im…
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…
ZePT: Zero-Shot Pan-Tumor Segmentation via Query-Disentangling and Self-Prompting
Yankai Jiang, Zhongzhen Huang, Rongzhao Zhang +2
The long-tailed distribution problem in medical image analysis reflects a high prevalence of common conditions and a low prevalence of rare ones, which poses a significant challeng…
Automatic lobe segmentation using attentive cross entropy and end-to-end fissure generation
Qi Su, Na Wang, Jiawen Xie +2
The automatic lung lobe segmentation algorithm is of great significance for the diagnosis and treatment of lung diseases, however, which has great challenges due to the incompleten…
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…
KiUT: Knowledge-injected U-Transformer for Radiology Report Generation
Zhongzhen Huang, Xiaofan Zhang, Shaoting Zhang
Radiology report generation aims to automatically generate a clinically accurate and coherent paragraph from the X-ray image, which could relieve radiologists from the heavy burden…
MidMed: Towards Mixed-Type Dialogues for Medical Consultation
Xiaoming Shi, Zeming Liu, Chuan Wang +4
Most medical dialogue systems assume that patients have clear goals (medicine querying, surgical operation querying, etc.) before medical consultation. However, in many real scenar…
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…
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…
Large-scale Gastric Cancer Screening and Localization Using Multi-task Deep Neural Network
Hong Yu, Xiaofan Zhang, Lingjun Song +20
Gastric cancer is one of the most common cancers, which ranks third among the leading causes of cancer death. Biopsy of gastric mucosa is a standard procedure in gastric cancer scr…
Heterogeneous Memory Enhanced Multimodal Attention Model for Video Question Answering
Chenyou Fan, Xiaofan Zhang, Shu Zhang +3
In this paper, we propose a novel end-to-end trainable Video Question Answering (VideoQA) framework with three major components: 1) a new heterogeneous memory which can effectively…
Embedding Label Structures for Fine-Grained Feature Representation
Xiaofan Zhang, Feng Zhou, Yuanqing Lin +1
Recent algorithms in convolutional neural networks (CNN) considerably advance the fine-grained image classification, which aims to differentiate subtle differences among subordinat…