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Spatially Localized Atlas Network Tiles Enables 3D Whole Brain Segmentation from Limited Data [article]

Yuankai Huo, Zhoubing Xu, Katherine Aboud, Prasanna Parvathaneni, Shunxing Bao, Camilo Bermudez, Susan M. Resnick, Laurie E. Cutting, Bennett A. Landman
2018 arXiv   pre-print
In this paper, we propose the spatially localized atlas network tiles (SLANT) method to distribute multiple independent 3D fully convolutional networks to cover overlapped sub-spaces in a standard atlas  ...  Yet, few previous efforts have been made on detailed whole brain segmentation using 3D networks due to the following challenges: (1) fitting entire whole brain volume into 3D networks is restricted by  ...  In this paper, we propose the spatially localized atlas network tiles (SLANT) method for detailed whole brain segmentation (133 labels under BrainCOLOR protocol [6] ) by combining canonical medical image  ... 
arXiv:1806.00546v2 fatcat:ptpsn7qn35gujh4pc6xo2gmrma

3D whole brain segmentation using spatially localized atlas network tiles

Yuankai Huo, Zhoubing Xu, Yunxi Xiong, Katherine Aboud, Prasanna Parvathaneni, Shunxing Bao, Camilo Bermudez, Susan M. Resnick, Laurie E. Cutting, Bennett A. Landman
2019 NeuroImage  
In this work, we propose the spatially localized atlas network tiles (SLANT) method to distribute multiple independent 3D fully convolutional networks (FCN) for high-resolution whole brain segmentation  ...  Recently, deep convolution neural network (CNN) has been applied to whole brain segmentation.  ...  We appreciate the NIH S10 Shared Instrumentation Grant 1S10OD020154-01 (Smith), Vanderbilt IDEAS grant (Holly-Bockelmann, Walker, Meliler, Palmeri, Weller), and ACCRE's Big Data TIPs grant from Vanderbilt  ... 
doi:10.1016/j.neuroimage.2019.03.041 pmid:30910724 pmcid:PMC6536356 fatcat:3uq5pbxd4jcntguwpujlneyfgu

CEREBRUM-7T: fast and fully-volumetric brain segmentation of out-of-the-scanner 7T MR volumes [article]

Michele Svanera, Sergio Benini, Dennis Bontempi, Lars Muckli
2020 bioRxiv   pre-print
In this work, we design and test CEREBRUM-7T, an optimised end-to-end CNN architecture, that allows to segment a whole 7T T1w MRI brain volume at once, without the need of partitioning it into 2D or 3D  ...  tiles.  ...  Acknowledgements This project has received funding from the European Union Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 785907 and 945539 (Human Brain  ... 
doi:10.1101/2020.07.07.191536 fatcat:jywisqltfbhxnfgkbd5z5djxte

Whole-brain mapping of behaviourally induced neural activation in mice

Dulcie A. Vousden, Jonathan Epp, Hiroyuki Okuno, Brian J. Nieman, Matthijs van Eede, Jun Dazai, Timothy Ragan, Haruhiko Bito, Paul W. Frankland, Jason P. Lerch, R. Mark Henkelman
2014 Brain Structure and Function  
However, current imaging methods are limited in their spatial resolution and/or ability to obtain brain-wide coverage of functional activity.  ...  processing algorithms to count the activated neurons and align the datasets to the Allen Mouse Brain Atlas; and statistical analysis to identify the network of activated brain regions evoked by behaviour  ...  JSPS (KIBAN to HO, WAKATE to HB) and from MHLW of Japan (to HB and HO).  ... 
doi:10.1007/s00429-014-0774-0 pmid:24760545 fatcat:ugc47xdwqremfirnmvxg2geo4i

Multiscale Exploration of Mouse Brain Microstructures Using the Knife-Edge Scanning Microscope Brain Atlas

Ji Ryang Chung, Chul Sung, David Mayerich, Jaerock Kwon, Daniel E. Miller, Todd Huffman, John Keyser, Louise C. Abbott, Yoonsuck Choe
2011 Frontiers in Neuroinformatics  
KESM whole-brain data sets now include Golgi (neuronal circuits), Nissl (soma distribution), and India ink (vascular networks).  ...  Recent advances in high-throughput, high-resolution 3D microscopy methods have enabled the imaging of whole small animal brains at a sub-micrometer resolution, potentially opening the road to full-blown  ...  DATABASES OF 3D RECONSTRUCTION OF NEURONS The low spatial resolution in existing whole-brain level brain maps and atlases have been pointed out as a major limitation.  ... 
doi:10.3389/fninf.2011.00029 pmid:22275895 pmcid:PMC3254184 fatcat:4amvlcja2fee3iavoukmihfo24

Automated analysis of whole brain vasculature using machine learning [article]

Mihail Ivilinov Todorov, Johannes C. Paetzold, Oliver Schoppe, Giles Tetteh, Velizar Efremov, Katalin Voelgyi, Marco Duering, Martin Dichgans, Marie Piraud, Bjoern Menze, Ali Erturk
2019 bioRxiv   pre-print
Tissue clearing methods enable imaging of intact biological specimens without sectioning. However, reliable and scalable analysis of such large imaging data in 3D remains a challenge.  ...  We systematically analyzed vascular features of the whole brains including their length, bifurcation points and radius at the micrometer scale by registering them to the Allen mouse brain atlas.  ...  However, such methods including local spatial regularization cannot segment large vascular networks across changing intensity distributions.  ... 
doi:10.1101/613257 fatcat:233qaac4mbf53h42x2vlrbs74u

Whole brain segmentation with full volume neural network

Yeshu Li, Jonathan Cui, Yilun Sheng, Xiao Liang, Jingdong Wang, Eric I-Chao Chang, Yan Xu
2021 Computerized Medical Imaging and Graphics  
Whole brain segmentation is an important neuroimaging task that segments the whole brain volume into anatomically labeled regions-of-interest.  ...  To address these issues, we propose to adopt a full volume framework, which feeds the full volume brain image into the segmentation network and directly outputs the segmentation result for the whole brain  ...  [2] developed a spatially localized atlas network tiles (SLANT) method, which is subvolume-based, where multiple spatially location-specific FCNs are trained in parallel, with auxiliary labels generated  ... 
doi:10.1016/j.compmedimag.2021.101991 pmid:34634548 fatcat:c4wq6dnmxvfyllgmkra7j3dg3i

CEREBRUM‐7T: Fast and Fully Volumetric Brain Segmentation of 7 Tesla MR Volumes

Michele Svanera, Sergio Benini, Dennis Bontempi, Lars Muckli
2021 Human Brain Mapping  
We here present CEREBRUM-7T, an optimised end-to-end convolutional neural network, which allows fully automatic segmentation of a whole 7T T1w MRI brain volume at once, without partitioning the volume,  ...  Despite recent efforts in brain imaging analysis, the literature lacks in accurate and fast methods for segmenting 7-tesla (7T) brain MRI.  ...  Similarly to CEREBRUM, also CEREBRUM-7T processes the whole brain volume as one, avoiding the drawbacks of the tiling process (Reina et al., 2020) , thus preserving both global and local contexts.  ... 
doi:10.1002/hbm.25636 pmid:34598307 pmcid:PMC8559470 fatcat:irzumdpcbnc67gwnb7p2x4d4dm

Split-Attention U-Net: A Fully Convolutional Network for Robust Multi-Label Segmentation from Brain MRI

Minho Lee, JeeYoung Kim, Regina EY Kim, Hyun Gi Kim, Se Won Oh, Min Kyoung Lee, Sheng-Min Wang, Nak-Young Kim, Dong Woo Kang, ZunHyan Rieu, Jung Hyun Yong, Donghyeon Kim (+1 others)
2020 Brain Sciences  
Multi-label brain segmentation from brain magnetic resonance imaging (MRI) provides valuable structural information for most neurological analyses.  ...  Therefore, we introduce Split-Attention U-Net (SAU-Net), a convolutional neural network with skip pathways and a split-attention module that segments brain MRI scans.  ...  Brain Sci. 2020, 10, 974  ... 
doi:10.3390/brainsci10120974 pmid:33322640 pmcid:PMC7764312 fatcat:rge2dyuogvggfbcyxaxb37o4ra

AssemblyNet: A large ensemble of CNNs for 3D Whole Brain MRI Segmentation [article]

Pierrick Coupé, Boris Mansencal, Michaël Clément, Rémi Giraud, Baudouin Denis de Senneville, Vinh-Thong Ta, Vincent Lepetit, José V. Manjon
2019 arXiv   pre-print
Whole brain segmentation using deep learning (DL) is a very challenging task since the number of anatomical labels is very high compared to the number of available training images.  ...  To address this problem, previous DL methods proposed to use a single convolution neural network (CNN) or few independent CNNs.  ...  The NDAR dataset includes data from the NIH Pediatric MRI Data Repository created by the NIH MRI Study of Normal Brain Development.  ... 
arXiv:1911.09098v1 fatcat:yq5blqsxbzcenlikojkhphq5oq

Conventional and Deep Learning Methods for Skull Stripping in Brain MRI

Hafiz Zia Ur Rehman, Hyunho Hwang, Sungon Lee
2020 Applied Sciences  
brain.  ...  In this paper, the current methods of skull stripping have been divided into two distinct groups—conventional or classical approaches, and convolutional neural networks or deep learning approaches.  ...  To solve those two problems, the author proposed the spatially localized atlas network tiles (SLANT) method. Multiple spatially distributed networks were used to overcome the spatial limitation.  ... 
doi:10.3390/app10051773 fatcat:nwp2z2y4jzgoxinv7sfppbfrfa

Quantitative whole-brain 3D imaging of tyrosine hydroxylase-labelled neuron architecture in the mouse MPTP model of Parkinson's disease

Urmas Roostalu, Casper B. G. Salinas, Ditte D. Thorbek, Jacob L. Skytte, Katrine Fabricius, Pernille Barkholt, Linu M. John, Vanessa Isabell Jurtz, Lotte Bjerre Knudsen, Jacob Jelsing, Niels Vrang, Henrik H. Hansen (+1 others)
2019 Disease Models & Mechanisms  
In conclusion, mouse whole-brain 3D imaging is ideal for unbiased automated counting and densitometric analysis of TH-positive cells.  ...  However, conventional immunohistochemical techniques applied to tissue sections have inherent limitations with respect to loss of 3D resolution, yielding insufficient information on the architecture of  ...  data imported from Allen Mouse Brain Atlas and mapped into the same spatial reference map as for TH protein expression.  ... 
doi:10.1242/dmm.042200 pmid:31704726 pmcid:PMC6899010 fatcat:jabg6gekyrfh7bklwqjdh64qqa

Browsing Multiple Subjects When the Atlas Adaptation Cannot Be Achieved via a Warping Strategy

Denis Rivière, Yann Leprince, Nicole Labra, Nabil Vindas, Ophélie Foubet, Bastien Cagna, Kep Kee Loh, William Hopkins, Antoine Balzeau, Martial Mancip, Jessica Lebenberg, Yann Cointepas (+2 others)
2022 Frontiers in Neuroinformatics  
The mainstream approach to exploit these atlases consists in spatially deforming each individual data onto a given atlas using dense deformation fields, which supposes the existence of a continuous mapping  ...  A "structural atlas" is thus a collection of annotated individual data with a common structure nomenclature.  ...  When multiple computers are used to render tiles in a network, each machine computes renderings for a limited number of brains (tiles), and TiledViz combines tiles on a single large screen, a wall, or  ... 
doi:10.3389/fninf.2022.803934 pmid:35311005 pmcid:PMC8928460 fatcat:jkcis5w2m5ay7e3pazbkbojtj4

Web tools for large-scale 3D biological images and atlases

Zsolt L Husz, Nicholas Burton, Bill Hill, Nestor Milyaev, Richard A Baldock
2012 BMC Bioinformatics  
The system provides an interactive visualisation for grey-level and colour 3D images including multiple image layers and spatial-data overlay.  ...  Here we solve the problem for 2D section views through archive data delivering compressed tiled images enabling users to browse through very-large volume data in the context of a standard web-browser.  ...  The Visible Male data is courtesy of National Library of Medicine, Visible Human Project, the CS17 embryo data is courtesy of the HUDSEN Electronic Atlas of the Developing Human Brain project, Newcastle  ... 
doi:10.1186/1471-2105-13-122 pmid:22676296 pmcid:PMC3412715 fatcat:rp7euhdijjahxk4xdt54qae6hi

Whole Brain Imaging with Serial Two-Photon Tomography

Stephen P. Amato, Feng Pan, Joel Schwartz, Timothy M. Ragan
2016 Frontiers in Neuroanatomy  
Furthermore, we provide a survey of the research that STP tomography has enabled in the field of neuroscience, provide examples of how this technology enables quantitative whole brain studies, and discuss  ...  Imaging entire mouse brains at submicron resolution has historically been a challenging undertaking and largely confined to the province of dedicated atlasing initiatives.  ...  As described in the text, plaque type was determined by morphological shape and the spatial location of each plaque was determined by atlasing the whole brain image against the Ma 2008 atlas.  ... 
doi:10.3389/fnana.2016.00031 pmid:27047350 pmcid:PMC4802409 fatcat:k4uvrmmkbbhyxejerh6c6kqara
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