Automatic quantification of CT images for traumatic brain injury

Koikkalainen J, Lötjönen J, Ledig C, Rueckert D, Tenovuo O, Menon D (2014)


Publication Type: Conference contribution

Publication year: 2014

Publisher: Institute of Electrical and Electronics Engineers Inc.

Pages Range: 125-128

Conference Proceedings Title: 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014

Event location: Beijing, CHN

ISBN: 9781467319591

DOI: 10.1109/isbi.2014.6867825

Abstract

Traumatic brain injury (TBI) is a major health problem and the most common cause of permanent disability in people under the age of 40 years. In this paper, we present a fully automatic framework for the analysis of acute computed tomography (CT) images in TBI. Different pathologies common in TBI are quantified and all the information is combined for clinical outcome prediction in individual patients. We propose a multi-template approach for the registration of CT data, which improves the robustness and accuracy of spatial normalization. This is especially important for noisy CT data and TBI images with large areas of pathology. The tissue segmentation methods we use have been optimized to deal with these challenges. The methods we describe have been evaluated on acute CTs from 104 TBI patients. We demonstrate on this dataset that the prediction of dichotomized favorable or unfavorable outcome can be made with an accuracy of 79%.

Involved external institutions

How to cite

APA:

Koikkalainen, J., Lötjönen, J., Ledig, C., Rueckert, D., Tenovuo, O., & Menon, D. (2014). Automatic quantification of CT images for traumatic brain injury. In 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 (pp. 125-128). Beijing, CHN: Institute of Electrical and Electronics Engineers Inc..

MLA:

Koikkalainen, Juha, et al. "Automatic quantification of CT images for traumatic brain injury." Proceedings of the 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, Beijing, CHN Institute of Electrical and Electronics Engineers Inc., 2014. 125-128.

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