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BrainSignsNET: A Deep Learning Model for 3D Anatomical Landmark Detection in the Human Brain Imaging
2025-08-05
radiology and imaging
Title + abstract only
View on medRxiv
Show abstract
Accurate detection of anatomical landmarks in brain Magnetic Resonance Imaging (MRI) scans is essential for reliable spatial normalization, image alignment, and quantitative neuroimaging analyses. In this study, we introduce BrainSignsNET, a deep learning framework designed for robust three-dimensional (3D) landmark detection. Our approach leverages a multi-task 3D convolutional neural network that integrates an attention decoder branch with a multi-class decoder branch to generate precise 3D he...
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