@inproceedings{2c93bbdddef74827a0553cacf31b6648,
title = "Longitudinal Multiple Sclerosis lesion segmentation using multi-view convolutional neural networks",
abstract = "Automatic segmentation of Multiple Sclerosis (MS) lesions is a challenging task due to their variability in shape, size, location and texture in Magnetic Resonance (MR) images. A reliable, automatic segmentation method can help diagnosis and patient follow-up while reducing the time consuming need of manual segmentation. In this paper, we present a fully automated method for MS lesion segmentation. The proposed method uses MR intensities and White Matter (WM) priors for extraction of candidate lesion voxels and uses Convolutional Neural Networks for false positive reduction. Our networks process longitudinal data, a novel contribution in the domain of MS lesion analysis. The method was tested on the ISBI 2015 dataset and obtained state-of-theart Dice results with the performance level of a trained human rater.",
keywords = "CNN, Longitudinal data, Multiple sclerosis, Segmentation",
author = "Ariel Birenbaum and Hayit Greenspan",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; 1st International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2016 and 2nd International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2016 held in conjunction with 19th International Conference ... ; Conference date: 21-10-2016 Through 21-10-2016",
year = "2016",
doi = "https://doi.org/10.1007/978-3-319-46976-8_7",
language = "الإنجليزيّة",
isbn = "9783319469751",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "58--67",
editor = "Zhi Lu and Vasileios Belagiannis and Tavares, {Joao Manuel R.S.} and Cardoso, {Jaime S.} and Andrew Bradley and Papa, {Joao Paulo} and Nascimento, {Jacinto C.} and Marco Loog and Julien Cornebise and Gustavo Carneiro and Diana Mateus and Loic Peter",
booktitle = "Deep Learning and Data Labeling for Medical Applications - 1st International Workshop, LABELS 2016, and 2nd International Workshop, DLMIA 2016 Held in Conjunction with MICCAI 2016, Proceedings",
}