@inproceedings{3c7e36398a8346eb8eb3ce790a147754,
title = "Siamese U-Net with Healthy Template for Accurate Segmentation of Intracranial Hemorrhage",
abstract = "Intracranial hemorrhage (ICH) is a fatal form of stroke which is caused by bleeding within or around the brain. Detection and quantification of hemorrhage are critical in the diagnosis and treatment of the disease. In this paper, we propose Siamese U-Net, to segment the abnormal regions of ICH more accurately from patients{\textquoteright} CT images. The Siamese U-Net is given a paired set of the patients{\textquoteright} CT images and a healthy template of the brain CT. We introduce the dissimilarity of hemorrhage regions from the healthy template to the long skip-connection in the U-Net architecture to emphasize the convolutional features of the abnormal regions by ICH. We evaluate the accuracy of the proposed architecture with a comparison of the baseline model. The proposed model shows significant improvement in Hausdorff distance (6.81%), dice score (9.07%), and volume percentage error (40.32%), compared to the baseline U-Net model. Regarding the healthy template, less both false-negative and false-positive regions are observed in the results of the Siamese U-Net. Consequently, the estimated blood volume by the Siamese U-Net is much closer to the actual volume than that of the baseline U-Net.",
keywords = "Brain, Convolutional neural network, Intracranial hemorrhage, Non-contrast CT, Siamese U-Net, Template",
author = "Doyoung Kwon and Jaesin Ahn and Jaeil Kim and Inchul Choi and Sungmoon Jeong and Lee, {Young Sup} and Jaechan Park and Minho Lee",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019 ; Conference date: 13-10-2019 Through 17-10-2019",
year = "2019",
doi = "10.1007/978-3-030-32248-9_94",
language = "English",
isbn = "9783030322472",
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 = "848--855",
editor = "Dinggang Shen and Pew-Thian Yap and Tianming Liu and Peters, {Terry M.} and Ali Khan and Staib, {Lawrence H.} and Caroline Essert and Sean Zhou",
booktitle = "Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings",
address = "Germany",
}