An Ensemble Approach for Uterine Pathology Classification in MRI Imaging Using Deep Learning-Reference-Cited by-同舟云学术

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An Ensemble Approach for Uterine Pathology Classification in MRI Imaging Using Deep Learning

Published:2023-11-15 Issue: Volume: Page:1672-1677
ISSN:
Container-title:2023 International Conference on Sustainable Communication Networks and Application (ICSCNA)
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Author:

Singh Tonjam Gunendra¹,Karthik B.¹,Wahengbam Monita²

Affiliation:

1. Bharath Institute of Higher Education and Research,Department of Electronics and Communication Engineering,Selaiyur, Chennai-126,Tamil Nadu,India

2. Bharath Institute of Higher Education and Research,Department of Computer Science and Engineering,Selaiyur, Chennai-126,Tamil Nadu,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10370002/10368600/10370073.pdf?arnumber=10370073

Reference18 articles.

1. MRI Based Radiomics Approach With Deep Learning for Prediction of Vessel Invasion in Early-Stage Cervical Cancer

2. Deep Learning using Pre-Brachytherapy MRI to Automatically Predict Applicator Induced Complex Uterine Deformation

3. Tumor Detection using Deep Learning in Organs Specific to Indian Predicament

4. Artificial Intelligence Technique for Gene Expression by Tumor RNA-Seq Data: A Novel Optimized Deep Learning Approach

5. Efficient Automatic Detection of Uterine Fibroids Based on the Scalable EfficientDet

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Identification of Uterine Cervical Cancer Using CNN Compared to ANFIS Approach on MRI Images;2024 International Conference on Advances in Data Engineering and Intelligent Computing Systems (ADICS);2024-04-18

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