Related Experiment Video For Fuzzy entropy
Updated: Feb 5, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
Published on: November 30, 2022
Thresholding for Medical Image Segmentation for Cancer using Fuzzy Entropy with Level Set Algorithm
Ismail Yaqub Maolood1, Yahya Eneid Abdulridha Al-Salhi1, Songfeng Lu1,2
1School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.
Abstract:
In this study, an effective means for detecting cancer region through different types of medical image segmentation are presented and explained. We proposed a new method for cancer segmentation on the basis of fuzzy entropy with a level set (FELs) thresholding. The proposed method was successfully utilized to segment cancer images and then efficiently performed the segmentation of test ultrasound image, brain MRI, and dermoscopy image compared with algorithms proposed in previous studies. Results showed an excellent performance of the proposed method in detecting cancer image segmentation in terms of accuracy, precision, specificity, and sensitivity measures.
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