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FPGA based preliminary CAD for kidney on IoT enabled portable ultrasound imaging system

机译:基于FPGA的基于IoT的便携式超声成像系统用于肾脏的初步CAD

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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 analyze many diseases. Lack of trained sonographers make ultrasound imaging diagnosis time consuming to detect any abnormality. Sometimes the problem cannot exactly be identified which may lead to error in diagnosis. Hence in this paper we present computer aided automatic detection of abnormality in kidney on the ultrasound system itself, to decrease the time for reports and not to depend on the sonographer. We classified the kidney as normal and abnormal case. Segment the kidney region and extract Intensity histogram features and Haralick features from Gray Level Cooccurnace Matrix (GLCM). These features are calculated for a set of large data containing both normal and abnormal cases. Abnormal case includes kidney stone, cyst and bacterial infection. Standard deviation for each parameter is observed, considered only those features with less deviation and implemented on FPGA Kintex board. If the range of mean value is 1.08 to 1.336, skewness is 2.882 to 7.708, Kurtosis is 1.06 to 71.152, Cluster Shade is 72 to 243, Homogeneity is 0.993 to 0.998, the observed kidney image is normal otherwise abnormal.
机译:超声成像是非侵入性的,已被广泛用于初步诊断,并为医生分析许多疾病提供了良好的空间。缺乏训练有素的超声医师,使超声成像诊断花费大量时间来检测任何异常。有时无法完全识别出可能导致诊断错误的问题。因此,在本文中,我们提出了一种在超声系统本身上的计算机辅助自动检测肾脏异常的方法,以减少报告时间,而不必依赖超声医师。我们将肾脏分为正常和异常病例。分割肾脏区域,并从灰度共生矩阵(GLCM)中提取强度直方图特征和Haralick特征。这些功能是针对包含正常和异常情况的一组大数据计算的。异常病例包括肾结石,囊肿和细菌感染。观察到每个参数的标准偏差,仅考虑偏差较小的那些功能,并在FPGA Kintex板上实现。如果平均值范围为1.08至1.336,偏度为2.882至7.708,峰度为1.06至71.152,簇状阴影为72至243,同质度为0.993至0.998,则观察到的肾脏图像正常,否则异常。

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