Particle Swarm Optimized Fuzzy CNN With Quantitative Feature Fusion for Ultrasound Image Quality Identification-Reference-Cited by-同舟云学术

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

Published:2022 Issue: Volume:10 Page:1-12
ISSN:2168-2372
Container-title:IEEE Journal of Translational Engineering in Health and Medicine
language:
Short-container-title:IEEE J. Transl. Eng. Health Med.

Author:

Hossain Muhammad Minoar¹^ORCID,Hasan Md. Mahmodul¹,Rahim Md. Abdur¹^ORCID,Rahman Mohammad Motiur¹,Yousuf Mohammad Abu²^ORCID,Al-Ashhab Samer³,Akhdar Hanan F.⁴^ORCID,Alyami Salem A.³^ORCID,Azad Akm⁵,Moni Mohammad Ali⁶^ORCID

Affiliation:

1. Department of Computer Science and Engineering, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh

2. Institute of Information Technology, Jahangirnagar University, Savar, Dhaka, Bangladesh

3. Department of Mathematics and Statistics, Faculty of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia

4. Department of Physics, Faculty of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia

5. Faculty of Science, Engineering and Technology, Swinburne University of Technology Sydney, Parramatta, NSW, Australia

6. School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, QLD, Australia

Funder

Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University through Research Group

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering,General Medicine

Link

http://xplorestaging.ieee.org/ielx7/6221039/9652399/09853521.pdf?arnumber=9853521

Reference49 articles.

1. The effects of the median filter with different window sizes for ultrasound image

2. Evolving Ensemble Models for Image Segmentation Using Enhanced Particle Swarm Optimization

3. A Novel Fuzzy-Based Convolutional Neural Network Method to Traffic Flow Prediction With Uncertain Traffic Accident Information

4. A multimodal convolutional neuro-fuzzy network for emotion understanding of movie clips

5. Finger print Analysis and Matching using fuzzy logic design

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