Authors
Sook-Lei Liew, Bethany P Lo, Miranda R Donnelly, Artemis Zavaliangos-Petropulu, Jessica N Jeong, Giuseppe Barisano, Alexandre Hutton, Julia P Simon, Julia M Juliano, Anisha Suri, Zhizhuo Wang, Aisha Abdullah, Jun Kim, Tyler Ard, Nerisa Banaj, Michael R Borich, Lara A Boyd, Amy Brodtmann, Cathrin M Buetefisch, Lei Cao, Jessica M Cassidy, Valentina Ciullo, Adriana B Conforto, Steven C Cramer, Rosalia Dacosta-Aguayo, Ezequiel De la Rosa, Martin Domin, Adrienne N Dula, Wuwei Feng, Alexandre R Franco, Fatemeh Geranmayeh, Alexandre Gramfort, Chris M Gregory, Colleen A Hanlon, Brenton G Hordacre, Steven A Kautz, Mohamed Salah Khlif, Hosung Kim, Jan S Kirschke, Jingchun Liu, Martin Lotze, Bradley J MacIntosh, Maria Mataró, Feroze B Mohamed, Jan E Nordvik, Gilsoon Park, Amy Pienta, Fabrizio Piras, Shane M Redman, Kate P Revill, Mauricio Reyes, Andrew D Robertson, Na Jin Seo, Surjo R Soekadar, Gianfranco Spalletta, Alison Sweet, Maria Telenczuk, Gregory Thielman, Lars T Westlye, Carolee J Winstein, George F Wittenberg, Kristin A Wong, Chunshui Yu
Publication date
2022/6/16
Journal
Scientific data
Volume
9
Issue
1
Pages
320
Publisher
Nature Publishing Group UK
Description
Accurate lesion segmentation is critical in stroke rehabilitation research for the quantification of lesion burden and accurate image processing. Current automated lesion segmentation methods for T1-weighted (T1w) MRIs, commonly used in stroke research, lack accuracy and reliability. Manual segmentation remains the gold standard, but it is time-consuming, subjective, and requires neuroanatomical expertise. We previously released an open-source dataset of stroke T1w MRIs and manually-segmented lesion masks (ATLAS v1.2, N = 304) to encourage the development of better algorithms. However, many methods developed with ATLAS v1.2 report low accuracy, are not publicly accessible or are improperly validated, limiting their utility to the field. Here we present ATLAS v2.0 (N = 1271), a larger dataset of T1w MRIs and manually segmented lesion masks that includes training (n = 655), test (hidden …
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Scholar articles
SL Liew, BP Lo, MR Donnelly… - Scientific data, 2022