173 citations · 442 across the 31 of their papers we have counts for
31 papers
Universal Semi-Supervised Learning for Medical Image Classification
Lie Ju, Yicheng Wu, Wei Feng +4
Semi-supervised learning (SSL) has attracted much attention since it reduces the expensive costs of collecting adequate well-labeled training data, especially for deep learning met…
EPVT: Environment-aware Prompt Vision Transformer for Domain Generalization in Skin Lesion Recognition
Siyuan Yan, Chi Liu, Zhen Yu +6
Skin lesion recognition using deep learning has made remarkable progress, and there is an increasing need for deploying these systems in real-world scenarios. However, recent resea…
Towards Trustable Skin Cancer Diagnosis via Rewriting Model's Decision
Siyuan Yan, Zhen Yu, Xuelin Zhang +5
Deep neural networks have demonstrated promising performance on image recognition tasks. However, they may heavily rely on confounding factors, using irrelevant artifacts or bias w…
Multimorbidity Content-Based Medical Image Retrieval Using Proxies
Yunyan Xing, Benjamin J. Meyer, Mehrtash Harandi +2
Content-based medical image retrieval is an important diagnostic tool that improves the explainability of computer-aided diagnosis systems and provides decision making support to h…
3D Matting: A Benchmark Study on Soft Segmentation Method for Pulmonary Nodules Applied in Computed Tomography
Lin Wang, Xiufen Ye, Donghao Zhang +9
Usually, lesions are not isolated but are associated with the surrounding tissues. For example, the growth of a tumour can depend on or infiltrate into the surrounding tissues. Due…
3D Matting: A Soft Segmentation Method Applied in Computed Tomography
Lin Wang, Xiufen Ye, Donghao Zhang +7
Three-dimensional (3D) images, such as CT, MRI, and PET, are common in medical imaging applications and important in clinical diagnosis. Semantic ambiguity is a typical feature of…
Skin Lesion Recognition with Class-Hierarchy Regularized Hyperbolic Embeddings
Zhen Yu, Toan Nguyen, Yaniv Gal +7
In practice, many medical datasets have an underlying taxonomy defined over the disease label space. However, existing classification algorithms for medical diagnoses often assume…
Unsupervised Domain Adaptive Fundus Image Segmentation with Category-level Regularization
Wei Feng, Lin Wang, Lie Ju +4
Existing unsupervised domain adaptation methods based on adversarial learning have achieved good performance in several medical imaging tasks. However, these methods focus only on…
Camera Adaptation for Fundus-Image-Based CVD Risk Estimation
Zhihong Lin, Danli Shi, Donghao Zhang +3
Recent studies have validated the association between cardiovascular disease (CVD) risk and retinal fundus images. Combining deep learning (DL) and portable fundus cameras will ena…
Flexible Sampling for Long-tailed Skin Lesion Classification
Lie Ju, Yicheng Wu, Lin Wang +5
Most of the medical tasks naturally exhibit a long-tailed distribution due to the complex patient-level conditions and the existence of rare diseases. Existing long-tailed learning…
Label uncertainty-guided multi-stream model for disease screening
Chi Liu, Zongyuan Ge, Mingguang He +1
The annotation of disease severity for medical image datasets often relies on collaborative decisions from multiple human graders. The intra-observer variability derived from indiv…
Medical Visual Question Answering: A Survey
Zhihong Lin, Donghao Zhang, Qingyi Tao +5
Medical Visual Question Answering~(VQA) is a combination of medical artificial intelligence and popular VQA challenges. Given a medical image and a clinically relevant question in…
Hierarchical Knowledge Guided Learning for Real-world Retinal Diseases Recognition
Lie Ju, Zhen Yu, Lin Wang +4
In the real world, medical datasets often exhibit a long-tailed data distribution (i.e., a few classes occupy the majority of the data, while most classes have only a limited numbe…
Evaluation of Various Open-Set Medical Imaging Tasks with Deep Neural Networks
Zongyuan Ge, Xin Wang
The current generation of deep neural networks has achieved close-to-human results on "closed-set" image recognition; that is, the classes being evaluated overlap with the training…
Early Melanoma Diagnosis with Sequential Dermoscopic Images
Zhen Yu, Jennifer Nguyen, Toan D Nguyen +6
Dermatologists often diagnose or rule out early melanoma by evaluating the follow-up dermoscopic images of skin lesions. However, existing algorithms for early melanoma diagnosis a…
Mutual Consistency Learning for Semi-supervised Medical Image Segmentation
Yicheng Wu, Zongyuan Ge, Donghao Zhang +4
In this paper, we propose a novel mutual consistency network (MC-Net+) to effectively exploit the unlabeled data for semi-supervised medical image segmentation. The MC-Net+ model i…
Unsupervised Domain Adaptation for Retinal Vessel Segmentation with Adversarial Learning and Transfer Normalization
Wei Feng, Lie Ju, Lin Wang +5
Retinal vessel segmentation plays a key role in computer-aided screening, diagnosis, and treatment of various cardiovascular and ophthalmic diseases. Recently, deep learning-based…
Medical Matting: A New Perspective on Medical Segmentation with Uncertainty
Lin Wang, Lie Ju, Xin Wang +8
It is difficult to accurately label ambiguous and complex shaped targets manually by binary masks. The weakness of binary mask under-expression is highlighted in medical image segm…
Relational Subsets Knowledge Distillation for Long-tailed Retinal Diseases Recognition
Lie Ju, Xin Wang, Lin Wang +5
In the real world, medical datasets often exhibit a long-tailed data distribution (i.e., a few classes occupy most of the data, while most classes have rarely few samples), which r…
Improving Medical Image Classification with Label Noise Using Dual-uncertainty Estimation
Lie Ju, Xin Wang, Lin Wang +6
Deep neural networks are known to be data-driven and label noise can have a marked impact on model performance. Recent studies have shown great robustness to classic image recognit…
Semi-supervised Left Atrium Segmentation with Mutual Consistency Training
Yicheng Wu, Minfeng Xu, Zongyuan Ge +2
Semi-supervised learning has attracted great attention in the field of machine learning, especially for medical image segmentation tasks, since it alleviates the heavy burden of co…
Melanoma Diagnosis with Spatio-Temporal Feature Learning on Sequential Dermoscopic Images
Zhen Yu, Jennifer Nguyen, Xiaojun Chang +5
Existing studies for automated melanoma diagnosis are based on single-time point images of lesions. However, melanocytic lesions de facto are progressively evolving and, moreover,…
Synergic Adversarial Label Learning for Grading Retinal Diseases via Knowledge Distillation and Multi-task Learning
Lie Ju, Xin Wang, Xin Zhao +4
The need for comprehensive and automated screening methods for retinal image classification has long been recognized. Well-qualified doctors annotated images are very expensive and…
Adversarial Pulmonary Pathology Translation for Pairwise Chest X-ray Data Augmentation
Yunyan Xing, Zongyuan Ge, Rui Zeng +4
Recent works show that Generative Adversarial Networks (GANs) can be successfully applied to chest X-ray data augmentation for lung disease recognition. However, the implausible an…