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Proceedings Paper

Automatic identification of intracranial hemorrhage in non-contrast CT with large slice thickness for trauma cases
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Paper Abstract

In this paper we propose a technique for automatic detection of intracranial hemorrhage (ICH) and acute intracranial hemorrhage (AIH) in brain Computed Tomography (CT) for trauma cases where no contrast can be applied and the CT has large slice thickness. ICH or AIH comprise of internal bleeding (intra-axial) or external (extra-axial) to the brain substance. Large bleeds like in intra-axial region are easy to diagnose whereas it can be challenging if small bleed occurs in extra-axial region particularly in the absence of contrast. Bleed region needs to be distinguished from bleed-look-alike brain regions which are abnormally bright falx and fresh flowing blood. We propose an algorithm for detection of brain bleed in various anatomical locations. A preprocessing step is performed to segment intracranial contents and enhancement of region of interests(ROIs). A number of bleed and bleed-look-alike candidates are identified from a set of 11 available cases. For each candidate texture based features are extracted from non-separable quincunx wavelet transform along with some other descriptive features. The candidates are randomly divided into a training and test set consisting of both bleed and bleed-look- alike. A supervised classifier is designed based on the training sample features. A performance accuracy of 96% is attained for the independent test candidates.

Paper Details

Date Published: 3 March 2009
PDF: 8 pages
Proc. SPIE 7260, Medical Imaging 2009: Computer-Aided Diagnosis, 726011 (3 March 2009); doi: 10.1117/12.812276
Show Author Affiliations
Pragnya Maduskar, Siemens Information Systems Ltd. (India)
Mausumi Acharyya, Siemens Information Systems Ltd. (India)


Published in SPIE Proceedings Vol. 7260:
Medical Imaging 2009: Computer-Aided Diagnosis
Nico Karssemeijer; Maryellen L. Giger, Editor(s)

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