2020
DOI: 10.1007/s12021-020-09481-9
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Evolution of Human Brain Atlases in Terms of Content, Applications, Functionality, and Availability

Abstract: Human brain atlases have been evolving tremendously, propelled recently by brain big projects, and driven by sophisticated imaging techniques, advanced brain mapping methods, vast data, analytical strategies, and powerful computing. We overview here this evolution in four categories: content, applications, functionality, and availability, in contrast to other works limited mostly to content. Four atlas generations are distinguished: early cortical maps, print stereotactic atlases, early digital atlases, and ad… Show more

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Cited by 36 publications
(40 citation statements)
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References 201 publications
(358 reference statements)
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“…Brain volumetrics were estimated from structural MRI using a previously published and validated segmentation algorithm. 32 , 33 , 34 , 35 …”
Section: Methodsmentioning
confidence: 99%
“…Brain volumetrics were estimated from structural MRI using a previously published and validated segmentation algorithm. 32 , 33 , 34 , 35 …”
Section: Methodsmentioning
confidence: 99%
“…The brain atlases are useful means for image partitioning by the individualized atlas (or atlases) superimposed on a scan, enabling in this way an ROI-based analysis and a comparison of the right and left cerebral hemispheres ( Nowinski, 2020a ). The number of image partitions varies from a few for some part of the brain (like only two in the MCA territory ( Maldijan et al, 2001 )) to many delineated by multiple complementary whole-brain atlases ( Nowinski, 2020b ).…”
Section: Discussionmentioning
confidence: 99%
“…Another direction is to combine the advantages of the SIM-based method ( Nowinski et al, 2013 ) and the multi-atlas guided method ( Nowinski, 2020a ) enhanced by the probabilistic stroke atlas ( Nowinski et al, 2014b ). In other words, the future development shall be directed toward the combination of the global methods with a high sampling both in space and density along with the employment of merged radiologic and neurologic data.…”
Section: Discussionmentioning
confidence: 99%
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“…The Fusion-Net proposed in 2019 by Kan et al [ 25 ] is particularly suitable for a general fusion unit of hand-drawn segmentation. In 2021, Rutherford et al [ 26 ] conducted a study on auto-mask failure due to poor quality raw data and investigated the identification errors caused by the quality and condition of medical images.…”
Section: Introductionmentioning
confidence: 99%