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NeuroNet: Fast and Robust Reproduction of Multiple Brain Image Segmentation Pipelines [article]

Martin Rajchl and Nick Pawlowski and Daniel Rueckert and Paul M. Matthews and Ben Glocker
2018 arXiv   pre-print
NeuroNet is a deep convolutional neural network mimicking multiple popular and state-of-the-art brain segmentation tools including FSL, SPM, and MALPEM.  ...  The network is trained on 5,000 T1-weighted brain MRI scans from the UK Biobank Imaging Study that have been automatically segmented into brain tissue and cortical and sub-cortical structures using the  ...  Introduction Accurate and robust structural segmentation of the brain is a key component in neuroimaging research.  ... 
arXiv:1806.04224v1 fatcat:ksp56mexbbggflmqaoxf25emnq

Improving segmentation reliability of multi-scanner brain images using a generative adversarial network

Kai Niu, Xueyan Li, Li Zhang, Zhensong Yan, Wei Yu, Peipeng Liang, Yan Wang, Ching-Po Lin, Huimao Zhang, Chunjie Guo, Kuncheng Li, Tianyi Qian
2021 Quantitative Imaging in Medicine and Surgery  
The newly developed QBrain method combined with GAN image transfer module and a SLANT-27 segmentation module was shown to improve the reliability of whole-brain automatic structural segmentation results  ...  and robustness compared to FS.  ...  Neuronet: fast and robust reproduction of whole brain segmentation using spatially localized atlas multiple brain image segmentation pipelines. arXiv network tiles.  ... 
doi:10.21037/qims-21-653 pmid:35284270 pmcid:PMC8899955 fatcat:rio22psyj5ghlare6a6nlpujue

ACNP 58th Annual Meeting: Poster Session III

2019 Neuropsychopharmacology  
The goal of this study was to use positron emission tomography (PET) brain imaging to investigate levels of prefrontal-limbic translocator protein (TSPO), a marker of microglia, in vivo in individuals  ...  Methods: A total of 23 individuals with PTSD (13M, 10F) and 26 trauma-exposed and non-exposed otherwise healthy individuals (18M, 8F) were imaged.  ...  As a comparison, we segmented the same scans using standard pipelines adapted for segmenting the infant brain -dHCP, SPM, and FAST.  ... 
doi:10.1038/s41386-019-0547-9 pmid:31801974 pmcid:PMC6957926 fatcat:dd7d43ysfvc5bbbstfl73szya4

Poster Session II

2015 Neuropsychopharmacology  
Images were preprocessed using multi-atlas skull stripping (MASS) followed by bias correction and tissue segmentation using multiplicative intrinsic component optimization (MICO).  ...  Each subject was registered to a 3D segmented and annotated rat brain atlas.  ...  multiple morbidities including obesity, diabetes, hypertension, and cardiovascular disease.  ... 
doi:10.1038/npp.2015.326 pmid:26632287 pmcid:PMC4672311 fatcat:ib64i5qmzngvxcpn5hznkcagie

ACNP 59th Annual Meeting: Poster Session II

2020 Neuropsychopharmacology  
Diffusion tensor imaging was completed to obtain measures of fractional anisotropy (FA), mean diffusivity (MD), and mode of the diffusion tensor (MO) of the white matter skeleton.  ...  Further, prior research has largely used unimodal approaches which do not take into account shared variability between brain measures (i.e., noting that brain gray and white matter likely covary).  ...  The brain was segmented into 352 cortical and subcortical regions using a publicly available CIFTI-space segmentation.  ... 
doi:10.1038/s41386-020-00891-6 pmid:33279935 pmcid:PMC7735200 fatcat:5nfeakhcfnhpnjyuvli34vyxxq

In-vivo MRI study of the effects of low-intensity rTMS on brain activity, chemistry and structure in rats [article]

Bhedita Jaya Seewoo
Magnetic resonance imaging (MRI) is one of only a few analytical methods that can assay in-vivo and longitudinal brain changes associated with rTMS treatment, with the added advantage of being a technique  ...  Overall, the results of this thesis reveal the ability of LI-rTMS to elicit changes in brain function, chemistry, and structure as well as in behaviour and gut microbiome.  ...  In 2008, an rTMS device produced by Neuronetics Inc.  ... 
doi:10.26182/5jgg-vt62 fatcat:6i4z3p7mfraa7kbnk2cngu4q7u

INTELLI 2014 Committee INTELLI Advisory Committee INTELLI 2014 Technical Program Committee

Pradeep Atrey, Jerzy Grzymala-Busse, Ingo Schwab, Firas Alnaimi, Paul Jeon, Samsung Electronics, Korea Kiyoshi Nitta, Yahoo Research, Japan, Stephan Puls, Paulo Couto, Yuichi Kawai (+122 others)
Technology and Research   unpublished
We hope that INTELLI 2014 was a successful international forum for the exchange of ideas and results between academia and industry and for the promotion of progress in the field of intelligent systems  ...  The diversity of systems and the spectrum of situations make it almost impossible for an end-user to handle the complexity of the challenges.  ...  Special thanks go to Roco de Nicola (CNR), for the work on SCEL [8], Michele Loreti (University of Florence) for the work on jRESP [9], and Carlo.  ...