Authors: Nazik Elsayed, Yousuf Babiker M. Osman, Cheng Li, Jiong Zhang, Shanshan Wang

Published on: April 02, 2024

Impact Score: 7.6

Arxiv code: Arxiv:2404.01671

Summary

• What is new: First comprehensive survey of deep learning techniques for segmenting vessels in both the heart and brain.
• Why this is important: Segmenting cardio-cerebrovascular structures from medical images is challenging due to thin or blurred vascular shapes, imbalanced distribution, and imaging artifacts.
• What the research proposes: Developing automated algorithms using deep learning techniques to effectively segment cardio-cerebrovascular structures.
• Results: Provides an up-to-date survey and analysis of deep learning approaches, highlighting the need for multi-modality label-efficient techniques.

Technical Details

Technological frameworks used: nan

Models used: Deep learning techniques

Data used: Cardio-cerebrovascular medical images

Potential Impact

Healthcare industry, medical imaging software companies, AI technology developers in the medical field

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