An integrated method for hemorrhage segmentation from brain CT Imaging

Authors:
H. S. Bhadauria;Annapurna Singh;M. L. Dewal
Affiliations:
Department of Electrical Engineering, Indian Institute of Technology, Roorkee 247667, India;Department of Computer Sc. & Engineering, G.B. Pant Engineering College, Pauri 246194, India;Department of Electrical Engineering, Indian Institute of Technology, Roorkee 247667, India
Venue:
Computers and Electrical Engineering
Year:
2013

Citing 8
Cited 0

Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations

Journal of Computational Physics
Geodesic Active Contours

International Journal of Computer Vision
A PDE-based fast local level set method

Journal of Computational Physics
An Adaptive Fuzzy Segmentation Algorithm for Three-Dimensional Magnetic Resonance Images

IPMI '99 Proceedings of the 16th International Conference on Information Processing in Medical Imaging
Level Set Evolution without Re-Initialization: A New Variational Formulation

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Abnormalities detection in serial computed tomography brain images using multi-level segmentation approach

Multimedia Tools and Applications
Active contours without edges

IEEE Transactions on Image Processing
Minimization of Region-Scalable Fitting Energy for Image Segmentation

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents an integrated segmentation method which combines the features of Fuzzy C-Mean (FCM) clustering and region-based active contour method. In the proposed method, FCM clustering is used to initialize the contour around the hemorrhagic region and then region-based active contour method propagates the initial contour towards the hemorrhage boundaries. Further, the FCM clustering is also used to estimate the contour propagation controlling parameters adaptively from the given image. The region-based active contour method uses the intensity information in the local regions as against the global regions in the traditional region-based active contour methods to guide the contour motion. The effectiveness of the proposed method is tested on the dataset of total 100 hemorrhagic brain CT images of 20 patients and the results are compared with region growing, FCM clustering and Chan & Vese methods. The proposed method yields the higher average values of the similarity indices namely sensitivity, specificity, accuracy and overlap metric as 79.93%, 99.10%, 84.83% and 88.84% respectively.