Advances in both imaging and computers have synergistically led to a rapid rise in the
potential use of artificial intelligence in various radiological imaging tasks, such as risk …

Tumors exhibit genomic and phenotypic heterogeneity, which has prognostic significance
and may influence response to therapy. Imaging can quantify the spatial variation in …

The increasing use of biomarkers in cancer have led to the concept of personalized
medicine for patients. Personalized medicine provides better diagnosis and treatment …

Over the last years, fractal and multifractal geometries were applied extensively in many
medical signal (1D, 2D or 3D) analysis applications like pattern recognition, texture analysis …

The role of breast image analysis in radiologists' interpretation tasks in cancer risk
assessment, detection, diagnosis, and treatment continues to expand. Breast image analysis …

In last three decades, fractal geometry (FG) has been the focus of attention by several
researchers owing to it exhibiting excellent properties and robust application with respect to …

This volume highlights the growing power and efficacy of the fractal geometry in
understanding how to analyze living phenomena and complex shapes. In March 2000 …

Background The assessment of a woman's risk for developing breast cancer has become
increasingly important for establishing personalized screening recommendations and …

Mammographic density has been strongly associated with increased risk of breast cancer.
Furthermore, density is inversely correlated with the accuracy of mammography and …

To evaluate deep learning in the assessment of breast cancer risk in which convolutional
neural networks (CNNs) with transfer learning are used to extract parenchymal …