Brain atrophy in Alzheimer's disease and aging
Thanks to its safety and accessibility, magnetic resonance imaging (MRI) is extensively used
in clinical routine and research field, largely contributing to our understanding of the …
in clinical routine and research field, largely contributing to our understanding of the …
The multimodal brain tumor image segmentation benchmark (BRATS)
In this paper we report the set-up and results of the Multimodal Brain Tumor Image
Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and …
Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and …
3D whole brain segmentation using spatially localized atlas network tiles
Detailed whole brain segmentation is an essential quantitative technique in medical image
analysis, which provides a non-invasive way of measuring brain regions from a clinical …
analysis, which provides a non-invasive way of measuring brain regions from a clinical …
[图书][B] Deep learning for medical image analysis
Deep Learning for Medical Image Analysis, Second Edition is a great learning resource for
academic and industry researchers and graduate students taking courses on machine …
academic and industry researchers and graduate students taking courses on machine …
Structural brain imaging in Alzheimer's disease and mild cognitive impairment: biomarker analysis and shared morphometry database
Magnetic resonance (MR) imaging is a powerful technique for non-invasive in-vivo imaging
of the human brain. We employed a recently validated method for robust cross-sectional and …
of the human brain. We employed a recently validated method for robust cross-sectional and …
Robust flow reconstruction from limited measurements via sparse representation
In many applications it is important to estimate a fluid flow field from limited and possibly
corrupt measurements. Current methods in flow estimation often use least squares …
corrupt measurements. Current methods in flow estimation often use least squares …
Local structure prediction with convolutional neural networks for multimodal brain tumor segmentation
P Dvořák, B Menze - Medical computer vision: Algorithms for big data …, 2016 - Springer
Most medical images feature a high similarity in the intensities of nearby pixels and a strong
correlation of intensity profiles across different image modalities. One way of dealing with …
correlation of intensity profiles across different image modalities. One way of dealing with …
AssemblyNet: A large ensemble of CNNs for 3D whole brain MRI segmentation
Whole brain segmentation of fine-grained structures using deep learning (DL) is a very
challenging task since the number of anatomical labels is very high compared to the number …
challenging task since the number of anatomical labels is very high compared to the number …
LINKS: Learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images
Segmentation of infant brain MR images is challenging due to insufficient image quality,
severe partial volume effect, and ongoing maturation and myelination processes. In the first …
severe partial volume effect, and ongoing maturation and myelination processes. In the first …
Automated segmentation of tissues using CT and MRI: a systematic review
Rationale and Objectives The automated segmentation of organs and tissues throughout the
body using computed tomography and magnetic resonance imaging has been rapidly …
body using computed tomography and magnetic resonance imaging has been rapidly …