Automatic Detection of White Matter Hyperintensities in Healthy Aging and Pathology Using Magnetic Resonance Imaging: A Review
Maria Eugenia Caligiuri,Paolo Perrotta,Antonio Augimeri,Federico Rocca,Aldo Quattrone,Andrea Cherubini +5 more
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TLDR
It is concluded that, in order to avoid artifacts and exclude the several sources of bias that may influence the analysis, an optimal method should comprise a careful preprocessing of the images, be based on multimodal, complementary data, take into account spatial information about the lesions and correct for false positives.Abstract:
White matter hyperintensities (WMH) are commonly seen in the brain of healthy elderly subjects and patients with several neurological and vascular disorders. A truly reliable and fully automated method for quantitative assessment of WMH on magnetic resonance imaging (MRI) has not yet been identified. In this paper, we review and compare the large number of automated approaches proposed for segmentation of WMH in the elderly and in patients with vascular risk factors. We conclude that, in order to avoid artifacts and exclude the several sources of bias that may influence the analysis, an optimal method should comprise a careful preprocessing of the images, be based on multimodal, complementary data, take into account spatial information about the lesions and correct for false positives. All these features should not exclude computational leanness and adaptability to available data.read more
Citations
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BIANCA (Brain Intensity AbNormality Classification Algorithm): A new tool for automated segmentation of white matter hyperintensities.
Ludovica Griffanti,Giovanna Zamboni,Aamira Khan,Linxin Li,Guendalina Bonifacio,Vaanathi Sundaresan,Ursula G. Schulz,Wilhelm Küker,Marco Battaglini,Peter M. Rothwell,Mark Jenkinson +10 more
TL;DR: The findings suggest that BIANCA, which will be freely available as part of the FSL package, is a reliable method for automated WMH segmentation in large cross-sectional cohort studies.
Journal ArticleDOI
Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities.
Mohsen Ghafoorian,Nico Karssemeijer,Tom Heskes,Inge W.M. van Uden,Clara I. Sánchez,Geert Litjens,Frank-Erik de Leeuw,Bram van Ginneken,Elena Marchiori,Bram Platel +9 more
TL;DR: This paper applies and compares the proposed architectures for segmentation of white matter hyperintensities in brain MR images on a large dataset and observes that the CNNs that incorporate location information substantially outperform a conventional segmentation method with handcrafted features as well asCNNs that do not integrate location information.
Journal ArticleDOI
Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge
Hugo J. Kuijf,Adrià Casamitjana,D. Louis Collins,Mahsa Dadar,Achilleas Georgiou,Mohsen Ghafoorian,Dakai Jin,April Khademi,Jesse Knight,Hongwei Li,Xavier Lladó,J. Matthijs Biesbroek,Miguel Luna,Qaiser Mahmood,Richard McKinley,Alireza Mehrtash,Sebastien Ourselin,Bo-yong Park,Hyunjin Park,Sang-Hyun Park,Simon Pezold,Elodie Puybareau,Jeroen de Bresser,Leticia Rittner,Carole H. Sudre,Sergi Valverde,Verónica Vilaplana,Roland Wiest,Yongchao Xu,Ziyue Xu,Guodong Zeng,Jianguo Zhang,Guoyan Zheng,Rutger Heinen,Christopher Chen,Wiesje M. van der Flier,Frederik Barkhof,Max A. Viergever,Geert Jan Biessels,Simon Andermatt,Mariana P. Bento,Matt Berseth,Mikhail Belyaev,M. Jorge Cardoso +43 more
TL;DR: There is a cluster of four methods that rank significantly better than the other methods, with one clear winner, and the inter-scanner robustness ranking shows that not all the methods generalize to unseen scanners.
Quantitative assessment of MRI lesion load in multiple sclerosis: A comparison of conventional spin-echo with fast fluid-attenuated inversion recovery
TL;DR: In this article, the authors compared a fast fluid-attenuated inversion recovery (fast-FLAIR) sequence to conventional spin-echo (CSE) in the evaluation of brain MRI lesion loads of seven patients with clinically definite multiple sclerosis.
Journal ArticleDOI
Aging of cerebral white matter.
Huan Liu,Yuanyuan Yang,Yuguo Xia,Wen Zhu,Rehana K. Leak,Zhishuo Wei,Jianyi Wang,Xiaoming Hu,Xiaoming Hu +8 more
TL;DR: The structural and functional alterations of WM in natural aging are summarized and how age-related WM changes influence the progression of various brain disorders, including ischemic and hemorrhagic stroke, TBI, Alzheimer's disease, and Parkinson's disease are discussed.
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