Systematic Review of Computing Approaches for Breast Cancer Detection Based Computer Aided Diagnosis Using Mammogram Images-Reference-Cited by-同舟云学术

Systematic Review of Computing Approaches for Breast Cancer Detection Based Computer Aided Diagnosis Using Mammogram Images

Published:2021-12-02 Issue: Volume: Page:1-47
ISSN:0883-9514
Container-title:Applied Artificial Intelligence
language:en
Short-container-title:Applied Artificial Intelligence

Author:

Zebari Dilovan Asaad¹,Ibrahim Dheyaa Ahmed²,Zeebaree Diyar Qader³,Haron Habibollah⁴^ORCID,Salih Merdin Shamal²,Damaševičius Robertas⁵^ORCID,Mohammed Mazin Abed⁶

Affiliation:

1. Center of Scientific Research and Development, Department of Computer Science, Nawroz University, Duhok, Iraq

2. Communications Engineering Techniques Department, Information Technology Collage, Imam Ja’afar Al-Sadiq University, Baghdad, Iraq

3. Research Center of Duhok Polytechnic University, Duhok, Iraq

4. School of Computing, Faculty of Engineering, University Teknologi Malaysia, Johor Bahru, Malaysia

5. Faculty of Applied Mathematics, Silesian University of Technology, Gliwice, Poland

6. Information Systems Department, College of Computer Science and Information Technology, University of Anbar, Ramadi, Iraq

Funder

funding associated with the work featured in this article

Publisher

Informa UK Limited

Subject

Artificial Intelligence

Link

https://www.tandfonline.com/doi/pdf/10.1080/08839514.2021.2001177

Reference160 articles.

1. Classification of Mammogram Images Using Multiscale all Convolutional Neural Network (MA-CNN)

2. A fully integrated computer-aided diagnosis system for digital X-ray mammograms via deep learning detection, segmentation, and classification

3. Evaluation of deep learning detection and classification towards computer-aided diagnosis of breast lesions in digital X-ray mammograms

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