1 citations · 1 across the 5 of their papers we have counts for
5 papers
Topology Optimization in Medical Image Segmentation with Fast Euler Characteristic
Liu Li, Qiang Ma, Cheng Ouyang +3
Deep learning-based medical image segmentation techniques have shown promising results when evaluated based on conventional metrics such as the Dice score or Intersection-over-Unio…
Universal Topology Refinement for Medical Image Segmentation with Polynomial Feature Synthesis
Liu Li, Hanchun Wang, Matthew Baugh +5
Although existing medical image segmentation methods provide impressive pixel-wise accuracy, they often neglect topological correctness, making their segmentations unusable for man…
Weakly Supervised Learning of Cortical Surface Reconstruction from Segmentations
Qiang Ma, Liu Li, Emma C. Robinson +2
Existing learning-based cortical surface reconstruction approaches heavily rely on the supervision of pseudo ground truth (pGT) cortical surfaces for training. Such pGT surfaces ar…
The Developing Human Connectome Project: A Fast Deep Learning-based Pipeline for Neonatal Cortical Surface Reconstruction
Qiang Ma, Kaili Liang, Liu Li +6
The Developing Human Connectome Project (dHCP) aims to explore developmental patterns of the human brain during the perinatal period. An automated processing pipeline has been deve…
Conditional Temporal Attention Networks for Neonatal Cortical Surface Reconstruction
Qiang Ma, Liu Li, Vanessa Kyriakopoulou +4
Cortical surface reconstruction plays a fundamental role in modeling the rapid brain development during the perinatal period. In this work, we propose Conditional Temporal Attentio…