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Second Level KT-1 Signature of CT Scanned Medical Images

Mayuri Razdan, Amit Kumar, Prabhat Munshi


The present study aims to extend the application of the First Kanpur Error Theorem (KT-1) in monitoring the progress of cancer treatment therapies. This progress is evaluated visually by the very popular diagnostic tools of computerized tomography (CT). A mathematical basis for “quantification” of these CT images is proposed here. The region of interest of the patient is scanned generally at different time intervals. Each stage of treatment has some specific KT-1 signature related with the CT image of that stage. In the present study this has been shown for two sets of CT image of human brain and liver. The first-level KT-1 signatures are used when projection data is available for real CT scans. When such data is not available then a “second-level” KT-1 signature is proposed. In medical CT imaging, projection data is generally not available to the radiologists/oncologists, hence the methodology outlined here can be used for the quantification of the effectiveness of treatment. The image reconstruction algorithm used in this study is the convolution back projection (CBP) technique that includes different filter functions. The two test cases considered here show the remarkable potential of this “second level” KT-1 signature in quantifying the state of disease before and after the treatment.


First Kanpur Error Theorem, Computerized Tomography, Convolution Backprojection Algorithm, Image Reconstruction

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