[HTML][HTML] Fetal brain mri atlases and datasets: a review
Fetal brain development is a complex process involving different stages of growth and
organization which are crucial for the development of brain circuits and neural connections …
organization which are crucial for the development of brain circuits and neural connections …
Automated methods for hippocampus segmentation: the evolution and a review of the state of the art
The segmentation of the hippocampus in Magnetic Resonance Imaging (MRI) has been an
important procedure to diagnose and monitor several clinical situations. The precise …
important procedure to diagnose and monitor several clinical situations. The precise …
Automated volumetry and regional thickness analysis of hippocampal subfields and medial temporal cortical structures in mild cognitive impairment
We evaluate a fully automatic technique for labeling hippocampal subfields and cortical
subregions in the medial temporal lobe in in vivo 3 Tesla MRI. The method performs …
subregions in the medial temporal lobe in in vivo 3 Tesla MRI. The method performs …
[PDF][PDF] Advanced normalization tools (ANTS)
Advanced Normalization Tools (ANTS) Page 1 Advanced Normalization Tools (ANTS)
Release 2.x Brian B. Avants 1 , Nick Tustison 2 and Hans Johnson 3 July 10, 2014 …
Release 2.x Brian B. Avants 1 , Nick Tustison 2 and Hans Johnson 3 July 10, 2014 …
BEaST: brain extraction based on nonlocal segmentation technique
Brain extraction is an important step in the analysis of brain images. The variability in brain
morphology and the difference in intensity characteristics due to imaging sequences make …
morphology and the difference in intensity characteristics due to imaging sequences make …
Deep label fusion: A generalizable hybrid multi-atlas and deep convolutional neural network for medical image segmentation
Deep convolutional neural networks (DCNN) achieve very high accuracy in segmenting
various anatomical structures in medical images but often suffer from relatively poor …
various anatomical structures in medical images but often suffer from relatively poor …
Multi-atlas segmentation with joint label fusion and corrective learning—an open source implementation
H Wang, PA Yushkevich - Frontiers in neuroinformatics, 2013 - frontiersin.org
Label fusion based multi-atlas segmentation has proven to be one of the most competitive
techniques for medical image segmentation. This technique transfers segmentations from …
techniques for medical image segmentation. This technique transfers segmentations from …
Volume increase in the dentate gyrus after electroconvulsive therapy in depressed patients as measured with 7T
Electroconvulsive therapy (ECT) is the most effective treatment for depression, yet its
working mechanism remains unclear. In the animal analog of ECT, neurogenesis in the …
working mechanism remains unclear. In the animal analog of ECT, neurogenesis in the …
Analysis of brain sub regions using optimization techniques and deep learning method in Alzheimer disease
D Chitradevi, S Prabha - Applied Soft Computing, 2020 - Elsevier
Automatic segmentation of brain sub regions such as White Matter (GM), Corpus Callosum
(CC), Grey Matter (WM) and Hippocampus (HC) is a challenging task due to the variations in …
(CC), Grey Matter (WM) and Hippocampus (HC) is a challenging task due to the variations in …
[HTML][HTML] Robust whole-brain segmentation: application to traumatic brain injury
We propose a framework for the robust and fully-automatic segmentation of magnetic
resonance (MR) brain images called “Multi-Atlas Label Propagation with Expectation …
resonance (MR) brain images called “Multi-Atlas Label Propagation with Expectation …