Detection and measurement of tubulitis in renal allograft rejection

John B. Hiller; Qi Chen; Jesse S. Jin; Yung Wang; James L. C. Yong

doi:10.1117/12.274089

25 April 1997 Detection and measurement of tubulitis in renal allograft rejection

John B. Hiller, Qi Chen, Jesse S. Jin, Yung Wang, James L. C. Yong

Author Affiliations +

Proceedings Volume 3034, Medical Imaging 1997: Image Processing; (1997) https://doi.org/10.1117/12.274089
Event: Medical Imaging 1997, 1997, Newport Beach, CA, United States

Abstract

Tubulitis is one of the most reliable signs of acute renal allograft rejection. It occurs when mononuclear cells are localized between the lining tubular epithelial cells with or without disruption of the tubular basement membrane. It has been found that tubulitis takes place predominantly in the regions of the distal convoluted tubules and the cortical collecting system. The image processing tasks are to find the tubule boundaries and to find the relative location of the lymphocytes and epithelial cells and tubule boundaries. The requirement for accuracy applies to determining the relative locations of the lymphocytes and the tubule boundaries. This paper will show how the different sizes and grey values of the lymphocytes and epithelial cells simplify their identification and location. Difficulties in finding the tubule boundaries image processing will be illustrated. It will be shown how proximate location of epithelial cells and the tubule boundary leads to distortion in determination of the calculated boundary. However, in tubulitis the lymphocytes and the tubule boundaries are proximate.In these cases the tubule boundary is adequately resolved and the image processing is satisfactory to determining relativity in location. An adaptive non-linear anisotropic diffusion process is presented for image filtering and segmentation. Multi-layer analysis is used to extract lymphocytes and tubulitis from images. This paper will discuss grading of tissue using the Banff system. The ability to use computer to use computer processing will be argued as obviating problems of reproducability of values for this classification. This paper will also feature discussion of alternative approaches to image processing and provide an assessment of their capability for improving the identification of the tubule boundaries.

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John B. Hiller, Qi Chen, Jesse S. Jin, Yung Wang, and James L. C. Yong "Detection and measurement of tubulitis in renal allograft rejection", Proc. SPIE 3034, Medical Imaging 1997: Image Processing, (25 April 1997); https://doi.org/10.1117/12.274089

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KEYWORDS

Image processing

Image filtering

Image segmentation

Diffusion

Anisotropic diffusion

Nonlinear filtering

Tissues

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