Automated Intracranial Hematoma Classification in Traumatic Brain Injury (TBI) Patients Using Meta-Heuristic Optimization Techniques

Vidhya, V and Raghavendra, U and Gudigar, Anjan and Kasula, Praneet and Chakole, Yashas and Hegde, Ajay and Menon, Girish and Ooi, Chin Wei and Ciaccio, Edward J and Acharya, Rajendra U (2022) Automated Intracranial Hematoma Classification in Traumatic Brain Injury (TBI) Patients Using Meta-Heuristic Optimization Techniques. Informatics, 9 (1). ISSN 2227-9709

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Abstract

Traumatic Brain Injury (TBI) is a devastating and life-threatening medical condition that can result in long-term physical and mental disabilities and even death. Early and accurate detec�tion of Intracranial Hemorrhage (ICH) in TBI is crucial for analysis and treatment, as the condition can deteriorate significantly with time. Hence, a rapid, reliable, and cost-effective computer-aided approach that can initially capture the hematoma features is highly relevant for real-time clinical diagnostics. In this study, the Gray Level Occurrence Matrix (GLCM), the Gray Level Run Length Matrix (GLRLM), and Hu moments are used to generate the texture features. The best set of discrimi�nating features are obtained using various meta-heuristic algorithms, and these optimal features are subjected to different classifiers. The synthetic samples are generated using ADASYN to compensate for the data imbalance. The proposed CAD system attained 95.74% accuracy, 96.93% sensitivity, and 94.67% specificity using statistical and GLRLM features along with KNN classifier. Thus, the developed automated system can enhance the accuracy of hematoma detection, aid clinicians in the fast interpretation of CT images, and streamline triage workflow

Item Type: Article
Uncontrolled Keywords: traumatic brain injury (TBI); intracranial hematoma; computed tomography; CAD; meta-heuristic algorithms
Subjects: Engineering > MIT Manipal > Computer Science and Engineering
Engineering > MIT Manipal > Instrumentation and Control
Medicine > KMC Manipal > Neuro Surgery
Depositing User: MIT Library
Date Deposited: 12 Jul 2022 05:02
Last Modified: 12 Jul 2022 05:02
URI: http://eprints.manipal.edu/id/eprint/158932

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