A Modified U-Net Based Framework for Automated Segmentation of Hippocampus Region in Brain MRI
Author:
Affiliation:
1. Department of Computer Engineering, University of Engineering and Technology, Taxila, Taxila, Pakistan
2. Department of Software Engineering, University of Engineering and Technology, Taxila, Taxila, Pakistan
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09734022.pdf?arnumber=9734022
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1. Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion Segmentation
2. Brain tumor segmentation with Deep Neural Networks
3. Comparison of AdaBoost and Support Vector Machines for Detecting Alzheimer's Disease Through Automated Hippocampal Segmentation
4. Accurate and Fully Automatic Hippocampus Segmentation Using Subject-Specific 3D Optimal Local Maps Into a Hybrid Active Contour Model
5. Measuring Size and Shape of the Hippocampus in MR Images Using a Deformable Shape Model
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