Evolving Fuzzy Image Segmentation with Self-Configuration

TL;DR

This paper introduces SC-EFIS, an improved evolving fuzzy image segmentation method that automatically estimates parameters and eliminates the need for auto-detection of regions of interest, enhancing automation and applicability.

Contribution

The paper presents SC-EFIS, a self-configuring version of EFIS that overcomes fixed parameter limitations and auto-detection dependency, making fuzzy image segmentation more automatic and versatile.

Findings

SC-EFIS achieves segmentation results comparable to EFIS.

SC-EFIS requires less manual parameter tuning.

The method enhances automation in medical image segmentation.

Abstract

Current image segmentation techniques usually require that the user tune several parameters in order to obtain maximum segmentation accuracy, a computationally inefficient approach, especially when a large number of images must be processed sequentially in daily practice. The use of evolving fuzzy systems for designing a method that automatically adjusts parameters to segment medical images according to the quality expectation of expert users has been proposed recently (Evolving fuzzy image segmentation EFIS). However, EFIS suffers from a few limitations when used in practice mainly due to some fixed parameters. For instance, EFIS depends on auto-detection of the object of interest for feature calculation, a task that is highly application-dependent. This shortcoming limits the applicability of EFIS, which was proposed with the ultimate goal of offering a generic but adjustable segmentation scheme. In this paper, a new version of EFIS is proposed to overcome these limitations. The new EFIS, called self-configuring EFIS (SC-EFIS), uses available training data to self-estimate the parameters that are fixed in EFIS. As well, the proposed SC-EFIS relies on a feature selection process that does not require auto-detection of an ROI. The proposed SC-EFIS was evaluated using the same segmentation algorithms and the same dataset as for EFIS. The results show that SC-EFIS can provide the same results as EFIS but with a higher level of automation.