114 citations · 230 across the 11 of their papers we have counts for
11 papers
Treatment Outcome Prediction for Intracerebral Hemorrhage via Generative Prognostic Model with Imaging and Tabular Data
Wenao Ma, Cheng Chen, Jill Abrigo +6
Intracerebral hemorrhage (ICH) is the second most common and deadliest form of stroke. Despite medical advances, predicting treat ment outcomes for ICH remains a challenge. This pa…
3DSAM-adapter: Holistic adaptation of SAM from 2D to 3D for promptable tumor segmentation
Shizhan Gong, Yuan Zhong, Wenao Ma +5
Despite that the segment anything model (SAM) achieved impressive results on general-purpose semantic segmentation with strong generalization ability on daily images, its demonstra…
Diffusion Model based Semi-supervised Learning on Brain Hemorrhage Images for Efficient Midline Shift Quantification
Shizhan Gong, Cheng Chen, Yuqi Gong +5
Brain midline shift (MLS) is one of the most critical factors to be considered for clinical diagnosis and treatment decision-making for intracranial hemorrhage. Existing computatio…
Test-time Adaptation with Calibration of Medical Image Classification Nets for Label Distribution Shift
Wenao Ma, Cheng Chen, Shuang Zheng +3
Class distribution plays an important role in learning deep classifiers. When the proportion of each class in the test set differs from the training set, the performance of classif…
Rapid model transfer for medical image segmentation via iterative human-in-the-loop update: from labelled public to unlabelled clinical datasets for multi-organ segmentation in CT
Wenao Ma, Shuang Zheng, Lei Zhang +2
Despite the remarkable success on medical image analysis with deep learning, it is still under exploration regarding how to rapidly transfer AI models from one dataset to another f…
Hierarchical Deep Network with Uncertainty-aware Semi-supervised Learning for Vessel Segmentation
Chenxin Li, Wenao Ma, Liyan Sun +4
The analysis of organ vessels is essential for computer-aided diagnosis and surgical planning. But it is not a easy task since the fine-detailed connected regions of organ vessel b…
Consistent Posterior Distributions under Vessel-Mixing: A Regularization for Cross-Domain Retinal Artery/Vein Classification
Chenxin Li, Yunlong Zhang, Zhehan Liang +3
Retinal artery/vein (A/V) classification is a critical technique for diagnosing diabetes and cardiovascular diseases. Although deep learning based methods achieve impressive result…
Multi-Task Neural Networks with Spatial Activation for Retinal Vessel Segmentation and Artery/Vein Classification
Wenao Ma, Shuang Yu, Kai Ma +3
Retinal artery/vein (A/V) classification plays a critical role in the clinical biomarker study of how various systemic and cardiovascular diseases affect the retinal vessels. Conve…
Multi-Site Infant Brain Segmentation Algorithms: The iSeg-2019 Challenge
Yue Sun, Kun Gao, Zhengwang Wu +30
To better understand early brain growth patterns in health and disorder, it is critical to accurately segment infant brain magnetic resonance (MR) images into white matter (WM), gr…
Multi-sequence Cardiac MR Segmentation with Adversarial Domain Adaptation Network
Jiexiang Wang, Hongyu Huang, Chaoqi Chen +3
Automatic and accurate segmentation of the ventricles and myocardium from multi-sequence cardiac MRI (CMR) is crucial for the diagnosis and treatment management for patients suffer…
Uncertainty-Guided Domain Alignment for Layer Segmentation in OCT Images
Jiexiang Wang, Cheng Bian, Meng Li +6
Automatic and accurate segmentation for retinal and choroidal layers of Optical Coherence Tomography (OCT) is crucial for detection of various ocular diseases. However, because of…