30 citations · 43 across the 15 of their papers we have counts for
16 papers
KidMesh: Computational Mesh Reconstruction for Pediatric Congenital Hydronephrosis Using Deep Neural Networks
Haoran Sun, Zhanpeng Zhu, Anguo Zhang +7
Pediatric congenital hydronephrosis (CH) is a common urinary tract disorder, primarily caused by obstruction at the renal pelvis-ureter junction. Magnetic resonance urography (MRU)…
ThermoSplat: Cross-Modal 3D Gaussian Splatting with Feature Modulation and Geometry Decoupling
Zhaoqi Su, Shihai Chen, Xinyan Lin +3
Multi-modal scene reconstruction integrating RGB and thermal infrared data is essential for robust environmental perception across diverse lighting and weather conditions. However,…
Towards the Automatic Segmentation, Modeling and Meshing of the Aortic Vessel Tree from Multicenter Acquisitions: An Overview of the SEG.A. 2023 Segmentation of the Aorta Challenge
Yuan Jin, Antonio Pepe, Gian Marco Melito +36
The automated analysis of the aortic vessel tree (AVT) from computed tomography angiography (CTA) holds immense clinical potential, but its development has been impeded by a lack o…
CineMyoPS: Segmenting Myocardial Pathologies from Cine Cardiac MR
Wangbin Ding, Lei Li, Junyi Qiu +6
Myocardial infarction (MI) is a leading cause of death worldwide. Late gadolinium enhancement (LGE) and T2-weighted cardiac magnetic resonance (CMR) imaging can respectively identi…
Aligning Multi-Sequence CMR Towards Fully Automated Myocardial Pathology Segmentation
Wangbin Ding, Lei Li, Junyi Qiu +5
Myocardial pathology segmentation (MyoPS) is critical for the risk stratification and treatment planning of myocardial infarction (MI). Multi-sequence cardiac magnetic resonance (M…
Multi-Modality Cardiac Image Computing: A Survey
Lei Li, Wangbin Ding, Liqun Huang +2
Multi-modality cardiac imaging plays a key role in the management of patients with cardiovascular diseases. It allows a combination of complementary anatomical, morphological and f…
Multi-Depth Boundary-Aware Left Atrial Scar Segmentation Network
Mengjun Wu, Wangbin Ding, Mingjin Yang +1
Automatic segmentation of left atrial (LA) scars from late gadolinium enhanced CMR images is a crucial step for atrial fibrillation (AF) recurrence analysis. However, delineating L…
Cross-Modality Multi-Atlas Segmentation via Deep Registration and Label Fusion
Wangbin Ding, Lei Li, Xiahai Zhuang +1
Multi-atlas segmentation (MAS) is a promising framework for medical image segmentation. Generally, MAS methods register multiple atlases, i.e., medical images with corresponding la…
Unsupervised Multi-Modality Registration Network based on Spatially Encoded Gradient Information
Wangbin Ding, Lei Li, Xiahai Zhuang +1
Multi-modality medical images can provide relevant or complementary information for a target (organ, tumor or tissue). Registering multi-modality images to a common space can fuse…
Automatic Pulmonary Artery-Vein Separation in CT Images using Twin-Pipe Network and Topology Reconstruction
Lin Pan, Yaoyong Zheng, Liqin Huang +5
With the development of medical computer-aided diagnostic systems, pulmonary artery-vein(A/V) separation plays a crucial role in assisting doctors in preoperative planning for lung…
Coarse-to-fine Airway Segmentation Using Multi information Fusion Network and CNN-based Region Growing
Jinquan Guo, Rongda Fu, Lin Pan +4
Automatic airway segmentation from chest computed tomography (CT) scans plays an important role in pulmonary disease diagnosis and computer-assisted therapy. However, low contrast…
Interpretative Computer-aided Lung Cancer Diagnosis: from Radiology Analysis to Malignancy Evaluation
Shaohua Zheng, Zhiqiang Shen, Chenhao Peia +6
Background and Objective:Computer-aided diagnosis (CAD) systems promote diagnosis effectiveness and alleviate pressure of radiologists. A CAD system for lung cancer diagnosis inclu…
Brain Tumor Segmentation Network Using Attention-based Fusion and Spatial Relationship Constraint
Chenyu Liu, Wangbin Ding, Lei Li +4
Delineating the brain tumor from magnetic resonance (MR) images is critical for the treatment of gliomas. However, automatic delineation is challenging due to the complex appearanc…
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…
Cross-Modality Multi-Atlas Segmentation Using Deep Neural Networks
Wangbin Ding, Lei Li, Xiahai Zhuang +1
Both image registration and label fusion in the multi-atlas segmentation (MAS) rely on the intensity similarity between target and atlas images. However, such similarity can be pro…
Multi-Modality Pathology Segmentation Framework: Application to Cardiac Magnetic Resonance Images
Zhen Zhang, Chenyu Liu, Wangbin Ding +4
Multi-sequence of cardiac magnetic resonance (CMR) images can provide complementary information for myocardial pathology (scar and edema). However, it is still challenging to fuse…