• RENJINI S

Cancer diagnosis through medical imaging continues to face challenges due to the irregularity, complexity, and noise present in biological tissues. Traditional image analysis methods often fall short in capturing the intricate structural patterns in medical data. This paper explores an interdisciplinary approach that integrates fractal geometry and fuzzy logic, focusing on the development and application of fuzzy fractal dimensions (FFD). By leveraging the descriptive power of fractals with the uncertainty modelling capabilities of fuzzy logic, FFD provides a powerful tool for analyzing medical images, particularly mammograms and mass spectrometry data, for early cancer detection. This paper reviews foundational theories, current methodologies, and recent advancements, and proposes a unified framework for applying FFD to various stages of cancer diagnosis. The results from existing studies highlight the promise of this approach in enhancing diagnostic accuracy and decision support in medical imaging.

Fuzzy fractal dimension, cancer detection, fractal geometry, fuzzy logic, image processing.

"ADVANCING CANCER DETECTION WITH FUZZY FRACTAL DIMENSIONS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 2, page no.472-479, February-2018, Available :http://www.jetir.org/papers/JETIR1802367.pdf

"ADVANCING CANCER DETECTION WITH FUZZY FRACTAL DIMENSIONS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 2, page no. pp472-479, February-2018, Available at : http://www.jetir.org/papers/JETIR1802367.pdf