Enhanced DeepLab Based Nerve Segmentation with Optimized Tuning
This work addresses nerve identification in medical imaging, showing incremental improvements over baseline models.
The study tackled nerve segmentation in medical imaging by optimizing a DeepLabV3-based pipeline with automated threshold fine-tuning, achieving a Dice Score of 0.78, IoU of 0.70, and Pixel Accuracy of 0.95 on ultrasound data.
Nerve segmentation is crucial in medical imaging for precise identification of nerve structures. This study presents an optimized DeepLabV3-based segmentation pipeline that incorporates automated threshold fine-tuning to improve segmentation accuracy. By refining preprocessing steps and implementing parameter optimization, we achieved a Dice Score of 0.78, an IoU of 0.70, and a Pixel Accuracy of 0.95 on ultrasound nerve imaging. The results demonstrate significant improvements over baseline models and highlight the importance of tailored parameter selection in automated nerve detection.