10 citations · 25 across the 17 of their papers we have counts for
11 papers · 1 filter
Principle-Guided Supervision for Interpretable Uncertainty in Medical Image Segmentation
An Sui, Yuzhu Li, Gunter Schumann +2
Uncertainty quantification complements model predictions by characterizing their reliability, which is essential for high-stakes decision making such as medical image segmentation.…
Uncertainty-Supervised Interpretable and Robust Evidential Segmentation
Yuzhu Li, An Sui, Fuping Wu +1
Uncertainty estimation has been widely studied in medical image segmentation as a tool to provide reliability, particularly in deep learning approaches. However, previous methods g…
InDeed: Interpretable image deep decomposition with guaranteed generalizability
Sihan Wang, Shangqi Gao, Fuping Wu +1
Image decomposition aims to analyze an image into elementary components, which is essential for numerous downstream tasks and also by nature provides certain interpretability to th…
MERIT: Multi-view evidential learning for reliable and interpretable liver fibrosis staging
Yuanye Liu, Zheyao Gao, Nannan Shi +4
Accurate staging of liver fibrosis from magnetic resonance imaging (MRI) is crucial in clinical practice. While conventional methods often focus on a specific sub-region, multi-vie…
A Reliable and Interpretable Framework of Multi-view Learning for Liver Fibrosis Staging
Zheyao Gao, Yuanye Liu, Fuping Wu +3
Staging of liver fibrosis is important in the diagnosis and treatment planning of patients suffering from liver diseases. Current deep learning-based methods using abdominal magnet…
Multi-Target Landmark Detection with Incomplete Images via Reinforcement Learning and Shape Prior
Kaiwen Wan, Lei Li, Dengqiang Jia +9
Medical images are generally acquired with limited field-of-view (FOV), which could lead to incomplete regions of interest (ROI), and thus impose a great challenge on medical image…
An Ensemble Method to Automatically Grade Diabetic Retinopathy with Optical Coherence Tomography Angiography Images
Yuhan Zheng, Fuping Wu, Bartłomiej W. Papież
Diabetic retinopathy (DR) is a complication of diabetes, and one of the major causes of vision impairment in the global population. As the early-stage manifestation of DR is usuall…
Random Style Transfer based Domain Generalization Networks Integrating Shape and Spatial Information
Lei Li, Veronika A. Zimmer, Wangbin Ding +4
Deep learning (DL)-based models have demonstrated good performance in medical image segmentation. However, the models trained on a known dataset often fail when performed on an uns…
Atrial Scar Quantification via Multi-scale CNN in the Graph-cuts Framework
Lei Li, Fuping Wu, Guang Yang +6
Late gadolinium enhancement magnetic resonance imaging (LGE MRI) appears to be a promising alternative for scar assessment in patients with atrial fibrillation (AF). Automating the…
Atrial scars segmentation via potential learning in the graph-cuts framework
Lei Li, Fuping Wu, Guang Yang +6
Late Gadolinium Enhancement Magnetic Resonance Imaging (LGE MRI) emerged as a routine scan for patients with atrial fibrillation (AF). However, due to the low image quality automat…
Atrial fibrosis quantification based on maximum likelihood estimator of multivariate images
Fuping Wu, Lei Li, Guang Yang +6
We present a fully-automated segmentation and quantification of the left atrial (LA) fibrosis and scars combining two cardiac MRIs, one is the target late gadolinium-enhanced (LGE)…