Rethinking alignment and uniformity in unsupervised image semantic segmentation

D Zhang, C Li, H Li, W Huang, L Huang… - Proceedings of the AAAI …, 2023 - ojs.aaai.org
Unsupervised image segmentation aims to match low-level visual features with semantic-
level representations without outer supervision. In this paper, we address the critical …

LIVE-Net: Comprehensive 3D vessel extraction framework in CT angiography

Q Sun, J Yang, S Zhao, C Chen, Y Hou, Y Yuan… - Computers in Biology …, 2023 - Elsevier
The extraction of vessels from computed tomography angiography (CTA) is significant in
diagnosing and evaluating vascular diseases. However, due to the anatomical complexity …

On the use of contrastive learning for standard-plane classification in fetal ultrasound imaging

G Migliorelli, MC Fiorentino, M Di Cosmo… - Computers in Biology …, 2024 - Elsevier
Background: To investigate the effectiveness of contrastive learning, in particular SimClr, in
reducing the need for large annotated ultrasound (US) image datasets for fetal standard …

Semi-supervised medical image segmentation guided by bi-directional constrained dual-task consistency

MZ Pan, XL Liao, Z Li, YW Deng, Y Chen, GB Bian - Bioengineering, 2023 - mdpi.com
Background: Medical image processing tasks represented by multi-object segmentation are
of great significance for surgical planning, robot-assisted surgery, and surgical safety …

Automating Vessel Segmentation in the Heart and Brain: A Trend to Develop Multi-Modality and Label-Efficient Deep Learning Techniques

N Elsayed, YBM Osman, C Li, J Zhang… - arXiv preprint arXiv …, 2024 - arxiv.org
Cardio-cerebrovascular diseases are the leading causes of mortality worldwide, whose
accurate blood vessel segmentation is significant for both scientific research and clinical …