Multi-Contrast Hippocampal Subfield Segmentation for Ultra-High Field 7T MRI Data using Deep Learning

التفاصيل البيبلوغرافية
العنوان: Multi-Contrast Hippocampal Subfield Segmentation for Ultra-High Field 7T MRI Data using Deep Learning
المؤلفون: Daniel Ramsing Lund, Mette Tøttrup Gade, Tina Jensen, Shaw, Thomas B., Maciej Plocharski, Lasse Riis ؘstergaard, Steffen Bollmann, Markus Barth
المصدر: Lund, D R, Gade, M T, Jensen, T, Shaw, T B, Plocharski, M, Østergaard, L R, Bollmann, S & Barth, M 2020, Multi-Contrast Hippocampal Subfield Segmentation for Ultra-High Field 7T MRI Data using Deep Learning . in Proceedings of the 2020 ISMRM & SMRT Virtual Conference & Exhibition, 08-14 August 2020 ., 3521, 2020 ISMRM & SMRT Virtual Conference & Exhibition, 08/08/2020 .
Aalborg University
سنة النشر: 2020
الوصف: Ultra-high field 7T MRI and the utilization of multiple MRI contrasts potentially enable a superior hippocampal subfield segmentation. A residual-dense fully convolutional neural network based on U-net, including a dilated-convolutional-block was implemented for hippocampal subfield segmentation. Two data sets were combined for training and mean DSC of 0.7723 was obtained. DSC was higher for larger subfields, which were undersegmented, while smaller subfields were oversegmented. Results were comparable to the atlas-based method ASHS, while providing a substantially faster processing time.
اللغة: English
URL الوصول: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::5cf1108446a690f17df4d77540b9a43a
https://vbn.aau.dk/da/publications/90bd3879-eb7b-4e39-a591-99ac05dcb511
Rights: RESTRICTED
رقم الانضمام: edsair.dedup.wf.001..5cf1108446a690f17df4d77540b9a43a
قاعدة البيانات: OpenAIRE