Implementation of artificial neural network and random iteration algorithm uses in medical images

Abstract EN

This research present a multiply connected neural network designed to estimate the fractal dimension (Df) using the Random Iteration Algorithm (IFSP).

Fractal analysis is a powerful shape recognition tool and has been applied to many pattern recognition problems.

Additionally, the one of the most adaptive Random Iteration Algorithm (IFSP) methods for estimating (Df).

The architecture presented separates the calculation of (Df) into two sections, a data sampling section and a linear regression section.

The data sampling section provides the ability to dyadic ally sample the data.

The linear regression section simply calculates the slope of the best line through the sampling results.

Instructional program was designed and built according to Knirk and Gustafson Design model, as one of the instructional design model in order to comprehension of the integrated ideas and concepts related to research.