Design of cognitive image filters for suppression of noise level in medical images. (July 2019)

• Record Type: Journal Article
• Authors: Prabu, S.; Balamurugan, V.; Vengatesan, K.
• Is Part Of: Measurement. Volume 141(2019)
• Page Start: 296
• Page End: 301
• Publication Date: 2019-07
• Subjects: Cognitive filters -- Medical images -- Denoising; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2019.04.037
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: Discovered the Drug Drug Interaction for HCC disease. Construct a GWIN subordinate upon gene articulation and in addition protein association grid. Improved singular value decomposition for reduction in dimensionality is done. Hepatocellular carcinoma subordinate upon the calculation based random walk. Abstract: Currently, medical image processing is used for the diagnosis of various diseases. But current technologies for medical image processing needs brighter light of research, since medical images are obtained from the various devices are affected by the different noises which in turn affects the accuracy of diagnosis/detection. Hence we propose the intelligent and cognitive image filters which works on the principle of adaptive selection theorem in which filters are selected based on the powerful fuzzy rule engine. The proposed filters are then compared with the previous filters and results obtained are more pivotal when compared with other filters.