C. Dhanalakshmi

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Accurate analysis of 2D echocardiographic images is vital for diagnosis and treatment of heart related diseases. For this task, extraction of cardiac borders must be carried out. In particular, automatic quantitative measurements of Left Ventricle (LV), Right Ventricle (RV), Left Atrium (LA), Right Atrium, Valve size, etc. are essential. We believe that(More)
An efficient K-Means clustering algorithm is proposed using the power of SQL in a relational Database Management environment. Further, this method is applied to segment 2D echocardiography images. We propose this method mainly to improve the speed of segmentation process for further clinical analysis and diagnosis (example: Left Ventricular (LV) boundary(More)
Doppler imaging allows evaluation of blood flow patterns, direction, and velocity. The color (red, blue, and mosaic) signify the direction of the blood flow. By analyzing this color Doppler, it is possible to detect heart diseases like mitral and aortic stenosis, mitral, tricuspid, and aortic regurgitation, and Left Ventricle (LV) hypertrophy. We present 3(More)
Content Based Image Retrieval (CBIR) is the application of computer vision techniques to retrieve the most visually similar images from the image database for any given query image. The visual characteristics of a disease carry diagnostic information and oftentimes visually similar images correspond to the same disease category. In this paper we aim at(More)
Variable latency adders have been recently proposed in literature. In variable latency adder unwanted interconnections also reduced compared with kogge-stone topology. Kogge-Stone adder consists of large number of black cells and many wire tracks. A variable latency adder employs speculation: the exact arithmetic function is replaced with an approximated(More)
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