Automatic non invasive kidney volume measurement based on ultrasound image

  • Authors:
  • Eko Supriyanto;Wan Mahani Hafizah;Yeoh Jing Wui;Adeela Arooj

  • Affiliations:
  • Diagnostics Research Group, Biotechnology Research Alliance, Universiti Teknologi Malaysia, Johor Bahru, Johor, Malaysia;Diagnostics Research Group, Biotechnology Research Alliance, Universiti Teknologi Malaysia, Johor Bahru, Johor, Malaysia;Diagnostics Research Group, Biotechnology Research Alliance, Universiti Teknologi Malaysia, Johor Bahru, Johor, Malaysia;Diagnostics Research Group, Biotechnology Research Alliance, Universiti Teknologi Malaysia, Johor Bahru, Johor, Malaysia

  • Venue:
  • Proceedings of the 15th WSEAS international conference on Computers
  • Year:
  • 2011

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Abstract

Variation in kidney sizes can be associated with different kidney diseases. Ultrasound is widely used in the measurement of kidney size in diagnostic process. However, the precision and accuracy of the result is low due to the manual measurement that is highly dependent on the skill and experience of the doctor. Hence, an automatic measurement system should be developed and implemented to measure the kidney size automatically from ultrasound image. One such method has been developed here in this study. First, samples of kidney ultrasound image were collected and analysed. Then, programming algorithm in which a combination of noise filtering method such as Gabor filter, Wiener filter, and sharpening methods were used to suppress the speckle noise on the ultrasound image while preserving the fine details. The kidney was then segmented from the image using Level set method in which the zero level set was evolved to minimize the overall energy function depending on the gradient flow. Comparison of pixel value was used to determine the maximum and minimum point which was utilized to find the length, width, and thickness. At last, volume of the kidney was calculated using ellipsoid formula. Few samples have been tested and the result showed that this system is viable and able to assist in the diagnosis of early stage kidney diseases.