activity
20202026
most citedFully Automated Left Atrium Segmentation from Anatomical Cine Long-axis MRI Sequences using Deep Convolutional Neural Network with Unscented Kalman Filter

31 citations · 83 across the 13 of their papers we have counts for

collaborators

14 papers

eess.IV2026

Native-Space 3D CarveMix for Multi-Site T1w Stroke Segmentation

Dexter Wen Jie Teo, Kumaradevan Punithakumar

Segmenting ischemic stroke lesions on T1-weighted (T1w) MRI acquired across different scanners and protocols without intensity standardization is difficult because lesions are subt…

eess.IV2025★ 5 cited

Extreme Cardiac MRI Analysis under Respiratory Motion: Results of the CMRxMotion Challenge

Kang Wang, Chen Qin, Zhang Shi +46

Deep learning models have achieved state-of-the-art performance in automated Cardiac Magnetic Resonance (CMR) analysis. However, the efficacy of these models is highly dependent on…

eess.IV2025

Accelerated 3D-3D rigid registration of echocardiographic images obtained from apical window using particle filter

Thanuja Uruththirakodeeswaran, Harald Becher, Michelle Noga +4

The perfect alignment of 3D echocardiographic images captured from various angles has improved image quality and broadened the field of view. This study proposes an accelerated seq…

eess.IV2024★ 1 cited

Neural Implicit Surface Reconstruction of Freehand 3D Ultrasound Volume with Geometric Constraints

Hongbo Chen, Logiraj Kumaralingam, Shuhang Zhang +9

Three-dimensional (3D) freehand ultrasound (US) is a widely used imaging modality that allows non-invasive imaging of medical anatomy without radiation exposure. Surface reconstruc…

eess.IV2023★ 11 cited

Efficient automatic segmentation for multi-level pulmonary arteries: The PARSE challenge

Gongning Luo, Kuanquan Wang, Jun Liu +27

Efficient automatic segmentation of multi-level (i.e. main and branch) pulmonary arteries (PA) in CTPA images plays a significant role in clinical applications. However, most exist…

cs.CV2022★ 17 cited

Biomedical image analysis competitions: The state of current participation practice

Matthias Eisenmann, Annika Reinke, Vivienn Weru +352

The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known abou…