Particle Swarm Optimized Fuzzy CNN With Quantitative Feature Fusion for Ultrasound Image Quality Identification

Particle Swarm Optimized Fuzzy CNN With Quantitative Feature Fusion for Ultrasound Image Quality Identification

Inherently ultrasound images are susceptible to noise which leads to several image quality issues. Hence, rating of an image’s quality is crucial since diagnosing diseases requires accurate and high-quality ultrasound images. This research presents an intelligent architecture to rate the...

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Bibliographic Details
Main Authors: Muhammad Minoar Hossain, Md. Mahmodul Hasan, Md. Abdur Rahim, Mohammad Motiur Rahman, Mohammad Abu Yousuf, Samer Al-Ashhab, Hanan F. Akhdar, Salem A. Alyami, Akm Azad, Mohammad Ali Moni
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Journal of Translational Engineering in Health and Medicine
Subjects:
Ultrasound image
quantitative feature extraction machine (QFEM)
particle swarm optimization (PSO)
feature fusion
fuzzy convolutional neural network
feature extraction
Online Access:https://ieeexplore.ieee.org/document/9853521/

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