A large, curated, open-source stroke neuroimaging dataset to improve lesion segmentation algorithms.
A large, curated, open-source stroke neuroimaging dataset to improve lesion segmentation algorithms.
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DOI：
10.1038/s41597-022-01401-7
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发表时间：
2022-06-16
期刊：
影响因子：
9.8
通讯作者：
Yu, Chunshui
中科院分区：
文献类型：
--
作者：
Liew, Sook-Lei;Lo, Bethany P.;Donnelly, Miranda R.;Zavaliangos-Petropulu, Artemis;Jeong, Jessica N.;Barisano, Giuseppe;Hutton, Alexandre;Simon, Julia P.;Juliano, Julia M.;Suri, Anisha;Wang, Zhizhuo;Abdullah, Aisha;Kim, Jun;Ard, Tyler;Banaj, Nerisa;Borich, Michael R.;Boyd, Lara A.;Brodtmann, Amy;Buetefisch, Cathrin M.;Cao, Lei;Cassidy, Jessica M.;Ciullo, Valentina;Conforto, Adriana B.;Cramer, Steven C.;Dacosta-Aguayo, Rosalia;de la Rosa, Ezequiel;Domin, Martin;Dula, Adrienne N.;Feng, Wuwei;Franco, Alexandre R.;Geranmayeh, Fatemeh;Gramfort, Alexandre;Gregory, Chris M.;Hanlon, Colleen A.;Hordacre, Brenton G.;Kautz, Steven A.;Khlif, Mohamed Salah;Kim, Hosung;Kirschke, Jan S.;Liu, Jingchun;Lotze, Martin;MacIntosh, Bradley J.;Mataro, Maria;Mohamed, Feroze B.;Nordvik, Jan E.;Park, Gilsoon;Pienta, Amy;Piras, Fabrizio;Redman, Shane M.;Revill, Kate P.;Reyes, Mauricio;Robertson, Andrew D.;Seo, Na Jin;Soekadar, Surjo R.;Spalletta, Gianfranco;Sweet, Alison;Telenczuk, Maria;Thielman, Gregory;Westlye, Lars T.;Winstein, Carolee J.;Wittenberg, George F.;Wong, Kristin A.;Yu, Chunshui
准确的病灶分割对于脑卒中康复研究中病灶负荷的量化和准确的图像处理至关重要。目前用于卒中研究的T1加权（T1 w）MRI的自动病变分割方法缺乏准确性和可靠性。手动分割仍然是黄金标准，但它耗时，主观，需要神经解剖学专业知识。我们之前发布了卒中T1 w MRI和手动分割病变掩模（ATLAS v1.2，N = 304）的开源数据集，以鼓励开发更好的算法。然而，使用ATLAS v1.2开发的许多方法报告准确性低，无法公开访问或未经适当验证，限制了其在该领域的实用性。在这里，我们展示了ATLAS v2.0（N = 1271），这是一个更大的T1 w MRI和手动分割病变掩模数据集，包括训练（n = 655），测试（隐藏掩模，n = 300）和泛化（隐藏MRI和掩模，n = 316）数据集。使用这个更大的样本进行算法开发应该会产生更强大的解决方案;隐藏的数据集允许通过分割挑战进行无偏的性能评估。我们预计，ATLAS v2.0将导致改进的算法，促进大规模中风研究。
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 masks, n = 300), and generalizability (hidden MRIs and masks, n = 316) datasets. Algorithm development using this larger sample should lead to more robust solutions; the hidden datasets allow for unbiased performance evaluation via segmentation challenges. We anticipate that ATLAS v2.0 will lead to improved algorithms, facilitating large-scale stroke research.
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影响因子：
4.8
作者：
Pustina D;Coslett HB;Turkeltaub PE;Tustison N;Schwartz MF;Avants B
通讯作者：
Avants B
Brainhack：开发一种开放，包容，社区驱动的神经科学的文化。
影响因子：
16.2
作者：
Gau, Remi;Noble, Stephanie;Heuer, Katja;Bottenhorn, Katherine L.;Bilgin, Isil P.;Yang, Yu-Fang;Huntenburg, Julia M.;Bayer, Johanna M. M.;Bethlehem, Richard A. I.;Rhoads, Shawn A.;Vogelbacher, Christoph;Borghesani, Valentina;Levitis, Elizabeth;Wang, Hao-Ting;Van den Bossche, Sofie;Kobeleva, Xenia;Legarreta, Jon Haitz;Guay, Samuel;Atay, Selim Melvin;Varoquaux, Gael P.;Huijser, Dorien C.;Sandstrom, Malin S.;Herholz, Peer;Nastase, Samuel A.;Badhwar, AmanPreet;Dumas, Guillaume;Schwab, Simon;Moia, Stefano;Dayan, Michael;Bassil, Yasmine;Brooks, Paula P.;Mancini, Matteo;Shine, James M.;O'Connor, David;Xie, Xihe;Poggiali, Davide;Friedrich, Patrick;Heinsfeld, Anibal S.;Riedl, Lydia;Toro, Roberto;Caballero-Gaudes, Cesar;Eklund, Anders;Garner, Kelly G.;Nolan, Christopher R.;Demeter, Damion V.;Barrios, Fernando A.;Merchant, Junaid S.;McDevitt, Elizabeth A.;Oostenveld, Robert;Craddock, R. Cameron;Rokem, Ariel;Doyle, Andrew;Ghosh, Satrajit S.;Nikolaidis, Aki;Stanley, Olivia W.;Urunuela, Eneko
通讯作者：
Urunuela, Eneko
DOI：
10.3390/s21061952
发表时间：
2021-03-10
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
Paing MP;Tungjitkusolmun S;Bui TH;Visitsattapongse S;Pintavirooj C
通讯作者：
Pintavirooj C
DOI：
10.1016/j.nicl.2017.06.016
发表时间：
2017
期刊：
NeuroImage. Clinical
影响因子：
--
作者：
Chen L;Bentley P;Rueckert D
通讯作者：
Rueckert D
影响因子：
10.9
作者：
Maier, Oskar;Menze, Bjoern H.;von der Gablentz, Janina;Hani, Levin;Heinrich, Mattias P.;Liebrand, Matthias;Winzeck, Stefan;Basit, Abdul;Bentley, Paul;Chen, Liang;Christiaens, Daan;Dutil, Francis;Egger, Karl;Feng, Chaolu;Glocker, Ben;Goetz, Michael;Haeck, Tom;Halme, Hanna-Leena;Havaei, Mohammad;Iftekharuddin, Khan M.;Jodoin, Pierre-Marc;Kamnitsas, Konstantinos;Kellner, Elias;Korvenoja, Antti;Larochelle, Hugo;Ledig, Christian;Lee, Jia-Hong;Maes, Frederik;Mahmood, Qaiser;Maier-Hein, Klaus H.;McKinley, Richard;Muschelli, John;Pal, Chris;Pei, Linmin;Rangarajan, Janaki Raman;Reza, Syed M. S.;Robben, David;Rueckert, Daniel;Salli, Eero;Suetens, Paul;Wang, Ching-Wei;Wilms, Matthias;Kirschke, Jan S.;Kraemer, Ulrike M.;Muente, Thomas F.;Schramme, Peter;Wiest, Roland;Handels, Heinz;Reyes, Mauricio
通讯作者：
Reyes, Mauricio