@inproceedings{c07848ac418e4b4fae487220f3e9a24b,
title = "Detection of Focal Cortical Dysplasia lesions in MR images",
abstract = "Focal cortical dysplasia (FCD) is the most common factor leading to intractable epilepsy. It is helpful for doctors to automatically detect the FCD lesion before the operation. In this study, two methods to detect and locate the lesion are proposed. The first method is based on the symmetrical characteristics of the brain image, and can approximately detect abnormal areas caused by FCD in Magnetic Resonance (MR) images. The second method involves detecting local highlighted areas in MR images based on the expectation-maximization (EM) algorithm. The two methods were applied to 15 specific MR images of 9 epileptic patients. The recognition accuracy of the symmetrical feature algorithm and EM algorithm was 80 % (12/15) and 100% (15/15), respectively, and the detection accuracy of the combination of two algorithms is 80%. The symmetrical feature algorithm can be applied to any of the axial or coronal MR images of the modality, and the EM algorithm is suitable for detecting the local hyperintense of the MR image. The two methods were able to detect lesion areas in MR images and achieve desirable results.",
keywords = "Detection, EM, FCD, MR image, Symmetrical feature",
author = "Cuixia Feng and Jun Zhang and Hulin Zhao and Zhibiao Cheng and Junhai Wen",
note = "Publisher Copyright: {\textcopyright} 2020 ACM.; 2nd International Conference on Big Data Engineering and Technology, BDET 2020 ; Conference date: 03-01-2020 Through 05-01-2020",
year = "2020",
month = jan,
day = "3",
doi = "10.1145/3378904.3378927",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "81--84",
booktitle = "BDET 2020 - 2020 2nd International Conference on Big Data Engineering and Technology",
}