A Novel Fuzzy-C Means Image Segmentation Model for MRI Brain Tumor Diagnosis

Publish Year: 1399
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:

JR_JACET-6-1_003

تاریخ نمایه سازی: 24 تیر 1399

Abstract:

Accurate segmentation of brain tumor plays a key role in the diagnosis of brain tumor. Preset and precise diagnosis of Magnetic Resonance Imaging (MRI) brain tumor is enormously significant for medical analysis. During the last years many methods have been proposed. In this research, a novel fuzzy approach has been proposed to classify a given MRI brain image as normal or cancer label and the intensity of the disease. The applied method first employed feature selection algorithms to extract features from images, and then followed by applying a median filter to reduce the dimensions of features. The brain MRI offers a valuable method to perform pre-and-post surgical evaluations, which are keys to define procedures and to verify their effects. The reduced dimension was submitted to a diagnosis algorithm. We retrospectively investigated a total of 19 treatment plans, each of whom has CT simulation and MRI images acquired during pretreatment. The dose distributions of the same treatment plans were calculated on original CT simulation images as ground truth, as well as on pseudo CT images generated from MRI images. The simulation results demonstrate that the proposed algorithm is promising.

Authors

Aref Safari

Department of Computer Engineering, Islamic Azad University of Rasht, Rasht, Iran

Danial Barazandeh

Department of Computer Engineering, Islamic Azad University, Rasht Branch

Seyed Ali Khalegh Pour

Department of Computer Engineering, Islamic Azad University, Rasht Branch

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