Computer Aided Abnormality Detection for Kidney on FPGA based IoT Enabled Portable Ultrasound Imaging System

K, Divya Krishna and Akkala, V and R, Bharath and P, Rajalakshmi and Mohammed, A M and Merchant, S N and Desai, U B (2016) Computer Aided Abnormality Detection for Kidney on FPGA based IoT Enabled Portable Ultrasound Imaging System. IRBM, 37 (4). pp. 189-197. ISSN 1959-0318 (Submitted)

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Ultrasound imaging has been widely used for preliminary diagnosis as it is non-invasive and has good scope for the doctors to analyse many diseases. Due to lack of trained radiologists in remote areas, tele-radiology is used to diagnose the scanned ultrasound data. Availability of online Radiographers and having communication facility for the portable ultrasound is an issue in tele-radiology for using ultrasound scanning in remote health-care. In this scenario, Computer Aided Diagnosis (CAD) will be beneficial in diagnosing the patients with minimal manual intervention. Hence, in this paper we propose FPGA based CAD algorithm for abnormality detection of kidney in ultrasound images. As a pre-processing, ultrasound image is denoised and region of interest of kidney in ultrasound image is segmented. Intensity histogram features and Haralick features are extracted from kidney region. The algorithm is implemented in two stages. In first stage, a Look Up Table (LUT) based approach is used to differentiate between normal and abnormal kidney images. If abnormality is detected then SVM classifier is used to further classify the presence of stone or cyst in kidney ultrasound image. SVM with Multi Layer Perceptron (MLP) kernel approach is used to detect the exact abnormality. The propose algorithm resulted with an accuracy of 98.14% in detecting the cyst or stone in kidney ultrasound images. The proposed algorithm is implemented on FPGA based Xilinx Kintex-7 board

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Item Type: Article
Uncontrolled Keywords: Intensity histogram features; Haralick features; FPGA; Cloud; Speckle; SVM kernel
Subjects: Others > Electricity
Divisions: Department of Electrical Engineering
Depositing User: Library Staff
Date Deposited: 28 Jan 2016 09:04
Last Modified: 03 Oct 2016 06:24
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