@inproceedings{4f05ea910be04367ac0f2fbddbf33362,
title = "Automated Detection of Cortical Lesions in Multiple Sclerosis Patients with 7T MRI",
abstract = "The automated detection of cortical lesions (CLs) in patients with multiple sclerosis (MS) is a challenging task that, despite its clinical relevance, has received very little attention. Accurate detection of the small and scarce lesions requires specialized sequences and high or ultra-high field MRI. For supervised training based on multimodal structural MRI at 7T, two experts generated ground truth segmentation masks of 60 patients with 2014 CLs. We implemented a simplified 3D U-Net with three resolution levels (3D U-Net-). By increasing the complexity of the task (adding brain tissue segmentation), while randomly dropping input channels during training, we improved the performance compared to the baseline. Considering a minimum lesion size of 0.75 μ L, we achieved a lesion-wise cortical lesion detection rate of 67\% and a false positive rate of 42\%. However, 393 (24\%) of the lesions reported as false positives were post-hoc confirmed as potential or definite lesions by an expert. This indicates the potential of the proposed method to support experts in the tedious process of CL manual segmentation.",
keywords = "CNN, Cortical lesions, MRI, Multiple sclerosis, Segmentation, Ultra-high field",
author = "\{La Rosa\}, Francesco and Beck, \{Erin S.\} and Ahmed Abdulkadir and Thiran, \{Jean Philippe\} and Reich, \{Daniel S.\} and Pascal Sati and \{Bach Cuadra\}, Meritxell",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020 ; Conference date: 04-10-2020 Through 08-10-2020",
year = "2020",
doi = "10.1007/978-3-030-59719-1\_57",
language = "English",
isbn = "9783030597184",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "584--593",
editor = "Martel, \{Anne L.\} and Purang Abolmaesumi and Danail Stoyanov and Diana Mateus and Zuluaga, \{Maria A.\} and Zhou, \{S. Kevin\} and Daniel Racoceanu and Leo Joskowicz",
booktitle = "Medical Image Computing and Computer Assisted Intervention {\textendash} MICCAI 2020 - 23rd International Conference, Proceedings",
address = "Germany",
}