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صفحه اصلی
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سی و سومین کنفرانس بین المللی مهندسی برق
Enhancing Fetal Brain MRI Segmentation with Adaptive Attention Mechanisms and Residual Blocks
نویسندگان :
Nazanin Valaee
1
Vajiheh Sabeti
2
1- دانشگاه الزهرا(س)
2- Alzahra University
کلمات کلیدی :
deep learning،Convolutional neural networks،Fetal brain segmentation،Medical image processing
چکیده :
Segmentation of fetal brain MRI is a critical task for assessing prenatal brain development, yet it remains one of the most challenging tasks due to low tissue contrast and motion artifacts. In this work, we propose a novel deep learning approach incorporating Adaptive Attention Mechanisms, Multi-Scale Feature Extraction, Residual Blocks, and an Edge-Aware Loss Function to improve segmentation accuracy. Our approach outperforms state-of-the-art techniques in seven crucial brain structures with an average Dice score of 0.90. The performance witnessed herein is better than that achieved by any of the previous models when trained for the same task, hence proving our model’s capability to deliver accurate and reliable segmentation of fetal brain MRI, thus aiding in improving clinical decision-making
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