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Jegannthan, R.
- Classification of Breast Cancer using Ridgelet based Feature Extraction
Abstract Views :165 |
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Authors
Affiliations
1 Department of Biomedical Engineering, Jerusalem College of Engineering, Chennai - 600100, Tamil Nadu, IN
2 Department of Biomedical Engineering, Bharath University, Chennai - 600073, Tamil Nadu, IN
1 Department of Biomedical Engineering, Jerusalem College of Engineering, Chennai - 600100, Tamil Nadu, IN
2 Department of Biomedical Engineering, Bharath University, Chennai - 600073, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 8, No 31 (2015), Pagination:Abstract
Breast cancer is the most common cancer all over the world. Ultrasound imaging is an effective tool in the detection of breast cancer because of its non ionizing radiation and low cost. This paper presents the automatic classification of breast cancer by ridgelet feature extraction method. Speckle noises in the ultrasound images are reduced by mean, Weiner and filtering techniques and region of interest is cropped from the filtered image. Statistical texture features are extracted by applying ridgelet transform. Using the feature set abnormalities are classified SVM classifier. The Performance of the feature selection methods best feature selection method is evaluated based on the results.Keywords
Denoising, Feature Extraction, Ridgelet Transform, SVMFull Text
- Study of Enzyme Kinetics using Capacitive Biosensor-An Alternate to Colorimeter
Abstract Views :182 |
PDF Views:0
Authors
Affiliations
1 Department of Biomedical Engineering, Bharath University, Chennai - 600073, Tamil Nadu, IN
1 Department of Biomedical Engineering, Bharath University, Chennai - 600073, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 8, No 31 (2015), Pagination:Abstract
A novel sensor approach based on measurement of changes in capacitance of an electrochemical cell produced during enzyme catalyzed formation of products is described. The electrochemical property such as capacitance of an electrolyte between electrochemical cell depends on its ionic compositions, in turn depends on the resulting ionic constituents caused by catalytic action of the enzyme. Generation of micromolar (μM) concentration of ionic species causes large changes in capacitance that is measurable in picofarad (pF) range in capacitive electrodes. Broad clinical analytical application of this technique is demonstrated in this report by application to diagnostically valued enzymes measurements like pyrophosphatases and phosphatases. Specific measurements of enzyme activities were achieved over the concentration range of 0.125 – 5.0 mM of respective substrates. The performance of the electrochemical sensor based enzyme biochemical assays were compared directly with identical assays employing spectrophotometric detection and found to match well.Keywords
Capacitance Changes, Electrochemical Cell, Enzyme Kinetics, Shigella ApyraseFull Text