AINeutralarXiv – CS AI · Jun 26/10
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ResNet-34 with Lightweight Decoder for Accurate and Efficient Segmentation of Fetal Brain MRI
Researchers have developed a ResNet-34-based deep learning model with a lightweight decoder for segmenting fetal brain tissues in MRI scans, achieving 97.37% accuracy and 90.33% mean Dice Similarity Coefficient. The model addresses critical challenges in prenatal diagnosis by handling fetal motion artifacts and anatomical variability while maintaining computational efficiency suitable for real-time clinical use.