Detection of cancer stages through fractal dimension analysis of tissue microarrays (TMA) via optical transmission microscopy
Liam Elkington, Prakash Adhikari, and Prabhakar Pradhan

TL;DR
This study investigates the use of fractal dimension analysis of tissue microarrays via optical microscopy to improve cancer diagnosis and staging accuracy, potentially leading to standardized and early detection methods.
Contribution
It demonstrates that fractal dimension analysis of tissue microarrays can reliably differentiate cancer stages, offering a new quantitative diagnostic approach.
Findings
Fractal dimension increases with cancer progression.
The method accurately differentiates cancer stages.
Potential for standardized cancer diagnosis system.
Abstract
Tissues are fractal due to its self-similar structure, and the fractal dimension change with the abnormalities such as in disease like cancer. The optical imaging of thin slices of tissue using transmission microscopy can produce an intensity distribution pattern proportional to its refractive index which represents the mass density distribution pattern of the tissues. The fractal dimension of tissue is calculated by analyzing this mass density distribution and is known to increase with the progression of carcinogenesis. This paper explores the viability of using this quantitative approach of fractal dimension analysis to create a standardized accurate cancer diagnosis test and staging which reduces the issues plaguing current testing methods. A commonality for most of the deadliest cancers is their lethality due to the difficulty in properly diagnosing them in the early stages or…
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Taxonomy
TopicsCell Image Analysis Techniques · Gene expression and cancer classification · Advanced Biosensing Techniques and Applications
