Detection and classification of Breast Cancer in Wavelet Sub-bands of Fractal Segmented Cancerous Zones.

Recent studies on wavelet transform and fractal modeling applied on mammograms for the detection of cancerous tissues indicate that microcalcifications and masses can be utilized for the study of the morphology and diagnosis of cancerous cases. It is shown that the use of fractal modeling, as applied to a given image, can clearly discern cancerous zones from noncancerous areas. In this paper, for fractal modeling, the original image is first segmented into appropriate fractal boxes followed by identifying the fractal dimension of each windowed section using a computationally efficient two-dimensional box-counting algorithm.

A model-based approach to stability analysis of autonomic-cardiac regulation.

This paper presents a model-based approach to analyze the stability of autonomic-cardiac regulation. In the proposed approach, a low-order lumped parameter model of autonomic-cardiac regulation is used to derive the system equilibria based on the measurements of heart rate and blood pressure, and then the stability margin associated with the equilibria is quantified via the Lyapunov's stability analysis method. A unique strength of the proposed approach is that it provides a quantitative measure of autonomic-cardiac stability via a computationally efficient analysis.

A novel approach to the design of an artificial bionic baroreflex.

This paper presents a computationally efficient method to design an artificial bionic baroreflex. This work is built upon a physiology-based mathematical model of autonomic-cardiac regulation describing the regulation of heart rate and blood pressure as well as a system identification technique to identify a subject-specific mathematical model for each subject. The control strategy to regulate blood pressure is developed based upon the in-vivo baroreflex mechanism.

Autonomic-cardiorespiratory regulation: a physiology-based mathematical model.

This paper presents a novel physiology-based mathematical model of autonomic-cardiorespiratory regulation described by a set of three nonlinear, coupled differential equations. We improved our previously proposed autonomic-cardiac regulation model by considering neuromechanical and mechanical coupling of cardiovascular and respiration systems including lung stretch-receptor reflex and venous return variation. We also introduced a differential equation describing respiration rate regulation which mainly originates in the medullary respiratory center.