Authors: Halid Ziya Yerebakan, Yoshihisa Shinagawa, Gerardo Hermosillo Valadez

Published on: April 29, 2024

Impact Score: 7.2

Arxiv code: Arxiv:2404.18731

Summary

• What is new: A new method employing a sparse sampling strategy for real-time voxel classification into multiple organs without accelerators.
• Why this is important: Organ segmentation is crucial in medical imaging but segmenting the entire volume is inefficient for limited areas of interest.
• What the research proposes: A data selection strategy that uses sparse sampling across a wide field of view for efficient classification, avoiding full volume segmentation.
• Results: Demonstrated potential for superior runtimes in medical imaging applications compared to existing segmentation techniques.

Technical Details

Technological frameworks used: nan

Models used: nan

Data used: nan

Potential Impact

Healthcare and medical imaging companies could benefit or need to adapt to this new, efficient organ segmentation method.

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