Temporal Ultrasound Image Enhancement for Kidney Diagnosis

Ultrasound imaging enables the physician to view the tissues and organs in abdominal region of the body without hazards of ionization compared to the other radiation based internal organ inspection devices. It provides highly accurate imaging of a kidney on suspected acute renal diseases. This thesis proposes temporal filtering methods to enhance the ultrasound images from ultrasound kidney video for the purposes of identification and diagnosis of kidney diseases by processing consecutive images of the acquired kidney video extending the spatial mean, median and weighted mean image filters to temporal dimension after cropping and aligning the image frames manually in MATLAB by Image Processing Toolbox to suppress speckle noise, and improve information content for a diagnosis by a medical doctor. The assessment of the filtered images by 10 medical experts indicates that the proposed temporal mean, median, and weighted mean filters improve the images better than the common spatial mean, median and weighted mean filters. The evaluators ranked the temporal weighted mean filtered images as the least preferable, while they scored the temporal median filtered images as the best preferable ultrasound images for the purpose of renal diagnosis. Keywords: Ultrasound Kidney Image, Image Enhancement by Video, Temporal Mean filter, Temporal Median Filter, Temporal Weighted Mean Filter.