Contrast enhancement for the detection of stroke signs in CT using PCA based image fusion

Jeena R. S.; Sukeshkumar A.; S. L. Shilu

doi:10.1117/12.2539659

14 August 2019 Contrast enhancement for the detection of stroke signs in CT using PCA based image fusion

Jeena R. S., Sukeshkumar A., S. L. Shilu

Proceedings Volume 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019); 111794F (2019) https://doi.org/10.1117/12.2539659
Event: Eleventh International Conference on Digital Image Processing (ICDIP 2019), 2019, Guangzhou, China

Abstract

Computed Tomography (CT) has been the typical imaging modality for the preliminary assessment of patients presenting with acute stroke signs. Since quantum noise degrades the visual quality of CT images, the existing contrast enhancement methods fail to provide a good contrast CT. Principal Component Analysis (PCA) based fusion of contrast and edge enhancement imaging has been implemented in this research work for highlighting the affected region during stroke diagnosis. A histogram modification technique called Adaptive gamma correction with weighting distribution (AGCWD) has been proposed for enhancing the contrast, and gradient operators are involved in enhancing the edges. No-reference-based performance estimation metrics are used for evaluating the objective quality of the enhanced CT images. Experimental result shows that the proposed PCA fusion method significantly enhances the visual perception of the CT images than those produced using existing methods by assisting physicians in the detection of stroke signs during the initial hours of occurrence.

Citation Download Citation

Jeena R. S., Sukeshkumar A., and S. L. Shilu "Contrast enhancement for the detection of stroke signs in CT using PCA based image fusion", Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111794F (14 August 2019); https://doi.org/10.1117/12.2539659

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KEYWORDS

Image fusion

Image enhancement

Computed tomography

Image quality

Principal component analysis

Medical imaging

Image contrast enhancement

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