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218453

The Impact of Data processing and Ensemble on Breast Cancer Detection Using Deep Learning

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Last updated: 24 Dec 2024

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Abstract

According to the World Health Organization, cancer is the second leading cause of mortality. Breast cancer is the most prevalent cancer diagnosed in women around the world. Breast cancer diagnostics range from mammograms to CT scans and ultrasounds, but a biopsy is the only way to know for sure if the suspicious cells detected in the breast are cancerous or not. This paper's main contribution is multi-fold. First, it proposes a deep learning approach to detect breast cancer from biopsy microscopy images. Deep convolution nets of various types are used. Second, the paper examines the effects of different data preprocessing techniques on the performance of deep learning models. Third, the paper introduces an ensemble method for aggregating the best models in order to improve performance. The experimental results revealed that Densenet169, Resnet50, and Resnet101 are the three best models achieving accuracy scores of 62%, 68%, and 85%, respectively. without data preprocessing. With the help of data augmentation and segmentation, the accuracy of these models increased by 20%, 17%, and 6%, respectively. Additionally, the ensemble learning technique improves the accuracy of the models even further. The results show that the best accuracy achieved is 92.5%.

DOI

10.21608/jocc.2022.218453

Keywords

Deep learning, breast cancer, Image classification

Authors

First Name

Ammar

Last Name

Mohamed

MiddleName

-

Affiliation

Faculty of Graduate Studies for Statistical Research Cairo University

Email

ammar@cu.edu.eg

City

-

Orcid

-

First Name

Eslam

Last Name

Amer

MiddleName

-

Affiliation

-

Email

eslam.amer@miuegypt.edu.eg

City

-

Orcid

-

First Name

sara

Last Name

Noor Eldin

MiddleName

-

Affiliation

Misr International university

Email

sara@miuegypt.edu.eg

City

-

Orcid

-

First Name

jana

Last Name

khaled

MiddleName

-

Affiliation

Department of Computer Science, Misr International University, Cairo, Egypt

Email

jana.khaled@miuegypt.edu.eg

City

-

Orcid

-

First Name

Maysoon

Last Name

Hossam

MiddleName

-

Affiliation

Department of Computer Science, Misr International University, Cairo, Egypt

Email

maysoon.hossam@miuegypt.edu.eg

City

-

Orcid

-

First Name

Noha

Last Name

Elmasry

MiddleName

-

Affiliation

Department of Computer Science ,Faculty of Computer Science , Misr International University, Cairo, Egypt

Email

noha.elmasry@miuegypt.edu.eg

City

-

Orcid

-

First Name

Ganna Tamer

Last Name

Adnan

MiddleName

-

Affiliation

Department of Computer Science , Faculty of Computer Science , Misr International University , Cairo , Egypt

Email

gannatullah1709438@miuegypt.edu.eg

City

-

Orcid

-

Volume

1

Article Issue

1

Related Issue

31132

Issue Date

2022-02-01

Receive Date

2022-01-05

Publish Date

2022-02-01

Page Start

27

Page End

37

Online ISSN

2636-3577

Article File

JOCC_Volume 1_Issue 1_Pages 27-37.pdf

PDF . 697.0kB

Link

https://jocc.journals.ekb.eg/article_218453.html

Detail API

https://jocc.journals.ekb.eg/service?article_code=218453

Order

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Type

Original Article

Type Code

731

Publication Type

Journal

Publication Title

Journal of Computing and Communication

Publication Link

https://jocc.journals.ekb.eg/

MainTitle

The Impact of Data processing and Ensemble on Breast Cancer Detection Using Deep Learning

Details

Type

Article

Created At

22 Jan 2023