# Artificial Neural Network Fuzzy Inference System (ANFIS) For Brain Tumor Detection

Source: [Artificial Neural Network Fuzzy Inference System (ANFIS) For Brain Tumor Detection](<https://www.sota2.com/research/paper/68fa60ba1e209131ce9f0c6e>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T19:45:32.888Z

Authors: Minakshi Sharma

Published: 2012-12-01T03:58:09.000Z

## Abstract

Detection and segmentation of Brain tumor is very important because it provides anatomical information of normal and abnormal tissues which helps in treatment planning and patient follow-up. There are number of techniques for image segmentation. Proposed research work uses ANFIS (Artificial Neural Network Fuzzy Inference System) for image classification and then compares the results with FCM (Fuzzy C means) and K-NN (K-nearest neighbor). ANFIS includes benefits of both ANN and the fuzzy logic systems. A comprehensive feature set and fuzzy rules are selected to classify an abnormal image to the corresponding tumor type. Experimental results illustrate promising results in terms of classification accuracy. A comparative analysis is performed with the FCM and K-NN to show the superior nature of ANFIS systems.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1212.0059>)

[PDF](<https://arxiv.org/pdf/1212.0059.pdf>)