TimeDistributed-CNN-LSTM: A Hybrid Approach Combining CNN and LSTM to Classify Brain Tumor on 3D MRI Scans Performing Ablation Study-Reference-Cited by-同舟云学术

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TimeDistributed-CNN-LSTM: A Hybrid Approach Combining CNN and LSTM to Classify Brain Tumor on 3D MRI Scans Performing Ablation Study

Published:2022 Issue: Volume:10 Page:60039-60059
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Montaha Sidratul¹^ORCID,Azam Sami²^ORCID,Rafid A. K. M. Rakibul Haque¹,Hasan Md. Zahid¹^ORCID,Karim Asif²^ORCID,Islam Ashraful³^ORCID

Affiliation:

1. Department of Computer Science and Engineering, Daffodil International University, Dhaka, Bangladesh

2. College of Engineering, IT and Environment, Charles Darwin University, Casuarina, NT, Australia

3. School of Computing and Informatics, University of Louisiana at Lafayette, Louisiana, LA, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09786658.pdf?arnumber=9786658

Reference56 articles.

1. A Time-Distributed Spatiotemporal Feature Learning Method for Machine Health Monitoring with Multi-Sensor Time Series

2. HYBRID-CNN: An Efficient Scheme for Abnormal Flow Detection in the SDN-Based Smart Grid

3. MRI assessment of sacroiliitis for the diagnosis of axial spondyloarthropathy: comparison of fat-saturated T2, STIR and contrast-enhanced sequences

4. Brain tumor segmentation based on deep learning and an attention mechanism using MRI multi-modalities brain images

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