ABSTRACT
Detection of a hemorrhage in CT scan slices is one of the crucial steps for a neurosurgeon to diagnose any abnormality and severity in the brain of a patient. It is usually time consuming as there are as many as 256 produced slices from a CT scan machine for each patient. In this paper, we introduce an automatic hemorrhage detection in brain CT slices using features-based approach. We employ decision tree based on 8 features to classify slices to two classes- with and without the sign of hemorrhage. The proposed method is tested on 1,451 CT scan slices and achieves a classification accuracy for up to 99% and it takes 0.12 second to detect slices.
- Carlos, S. K. and R. C. Louis, Intracerebral Hemorrhage. 1994, United States of America: Library of Congress Cataloging-in-Publication Data. 490.Google Scholar
- William, C. W., M. G. Christopher, and B. H. David, Trauma Critical Care. Vol. 2. 2007, United State of America: CRC Press.Google Scholar
- Santosh, H., Suryawanshi, and K. T. Jadhao, Smart Brain Hemorrhage Diagnosis Using Artificial Neural Networks. International Journal of Sicentific & Technology Research, 2015. 4 (10).Google Scholar
- Selvakumar, J., A. Lakshmi, and T. Arivoli, Brain Tumor Segmentation and Its Area Calculation in Brain MR Images using K-Mean Clustering and Fuzzy C-Mean Algorithm. International Conference on Advances In Engineering, Science and Management, 2012.Google Scholar
- Saini, S. and V. K. Banga, Haemorrhage Intracranial Segmentation in CT Brain Images using Sub-Blocking Rule Based Criteria. International Journal of Research in Engineering and Technology (IJRET), 2013. 2 (6).Google Scholar
- Alhawaimil, A., Segmentation of Brain Stroke Image. International Journal Of Advanced Research in Computer and Communication Engineering, 2015. 4 (9).Google Scholar
- Liu, R., C. L. Tan, and T. Y. Leong, Hemorrhage Slices Detection in Brain CT Images. 2000.Google Scholar
- John, N. and B.A. Jay, The Human Brain in Photographs and Diagrams. 4 ed. 2013, Library of Congress Cataloging-in-Publication Data: United State of America. 257.Google Scholar
- Sagar, B. T., K. Deepak, and P. Gopal, Image Processing (IP) Through Erosion and Dilation Methods. International Journal of Emerging Technology and Advanced Engineering, 2013. 3 (7).Google Scholar
Index Terms
- Fast Hemorrhage Detection in Brain CT Scan Slices Using Projection Profile Based Decision Tree
Recommendations
Efficient Brain Hemorrhage Detection on 3D CT Scans with Deep Neural Network
Future Data and Security EngineeringAbstractA brain hemorrhage is a type of stroke that can cause brain damage and can be life-threatening. The outcome of a brain bleed depends on its location inside the skull, the size of the bleed, and the duration between bleeding and treatment. Brain ...
Feature-Based Registration of Thorax CT Scan Slices
Radiologists need to find a position of a slice of one computed tomography (CT) scan in another scan. The image registration is a technique used to transform several images into one coordinate system and to compare them. Such transversal plane images ...
Segmentation of CT Brain Images Using Unsupervised Clusterings
In this paper, we present non-identical unsupervised clustering techniques for the segmentation of CT brain images. Prior to segmentation, we enhance the visualization of the original image. Generally, for the presence of abnormal regions in the brain ...
Comments