Author: Guillaume Chassagnon; Maria Vakalopoulou; Enzo Battistella; Stergios Christodoulidis; Trieu-Nghi Hoang-Thi; Severine Dangeard; Eric Deutsch; Fabrice Andre; Enora Guillo; Nara Halm; Stefany El Hajj; Florian Bompard; Sophie Neveu; Chahinez Hani; Ines Saab; Alienor Campredon; Hasmik Koulakian; Souhail Bennani; Gael Freche; Aurelien Lombard; Laure Fournier; Hippolyte Monnier; Teodor Grand; Jules Gregory; Antoine Khalil; Elyas Mahdjoub; Pierre-Yves Brillet; Stephane Tran Ba; Valerie Bousson; Marie-Pierre Revel; Nikos Paragios
Title: AI-Driven CT-based quantification, staging and short-term outcome prediction of COVID-19 pneumonia Document date: 2020_4_22
ID: nxm1jr0x_17
Snippet: Fifteen radiologists (GC, TNHT, SD, EG, NH, SEH, FB, SN, CH, IS, HK, SB, AC, GF and MB) with 1 to 7 years of experience in chest imaging participated in the data annotation which was conducted over a 2-week period. For the training and validation set for the COVID-19 radiological pattern segmentation, the whole CT examinations were manually annotated slice by slice using the open source software ITKsnap 1 . On each of the 23, 423 axial slices com.....
Document: Fifteen radiologists (GC, TNHT, SD, EG, NH, SEH, FB, SN, CH, IS, HK, SB, AC, GF and MB) with 1 to 7 years of experience in chest imaging participated in the data annotation which was conducted over a 2-week period. For the training and validation set for the COVID-19 radiological pattern segmentation, the whole CT examinations were manually annotated slice by slice using the open source software ITKsnap 1 . On each of the 23, 423 axial slices composing this dataset, all the COVID-19 related CT abnormalities (ground glass opacities, band consolidations, and reticulations) were segmented as a single class. Additionally, the whole lung was segmented to create another class (lung). To facilitate the collection of the ground truth for the lung anatomy, a preliminary lung segmentation was performed with Myrian XP-Lung software (version 1.19.1, Intrasense, Montpellier, France) and then manually corrected.
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