Multi-Classification of brain tumor based on deep CNN

Wadhah Ayadi; Wajdi Elhamzi; Mohamed Atri

doi:10.1109/SETIT54465.2022.9875468

Multi-Classification of brain tumor based on deep CNN

Wadhah Ayadi
, Wajdi Elhamzi
, Mohamed Atri

Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

In the last decades, brain tumors are considered one of the mortal cancers in the world. The right tumors detection and identification in the early phases have a significant role to select an accurate treatment. Due to the increasing number of patients and brain tumor types, the manual analyses of Magnetic Resonance Imaging (MRI) images represent a tiring routine and can lead to human errors. In the goal to surpass these problems, an automatic CAD system is needed. We discussed, in this paper, a new model to classify brain tumors using CNN. The suggested scheme is experimentally evaluated on a public dataset. The proposed approach yields a convincing performance compared to previous techniques based on the experimental results.

Original language	English
Title of host publication	2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	87-90
Number of pages	4
ISBN (Electronic)	9781728184425
DOIs	https://doi.org/10.1109/SETIT54465.2022.9875468
State	Published - 2022
Event	9th IEEE International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022 - Hammamet, Tunisia Duration: 28 May 2022 → 30 May 2022

Publication series

Name	2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022

Conference

Conference	9th IEEE International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022
Country/Territory	Tunisia
City	Hammamet
Period	28/05/22 → 30/05/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Classification
CNN
Deep Learning
MRI
Tumor

Access to Document

10.1109/SETIT54465.2022.9875468

Cite this

Ayadi, W., Elhamzi, W., & Atri, M. (2022). Multi-Classification of brain tumor based on deep CNN. In 2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022 (pp. 87-90). (2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SETIT54465.2022.9875468

Ayadi, Wadhah ; Elhamzi, Wajdi ; Atri, Mohamed. / Multi-Classification of brain tumor based on deep CNN. 2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 87-90 (2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022).

@inproceedings{2b39e9a336f94b2491c746879307ffaf,

title = "Multi-Classification of brain tumor based on deep CNN",

abstract = "In the last decades, brain tumors are considered one of the mortal cancers in the world. The right tumors detection and identification in the early phases have a significant role to select an accurate treatment. Due to the increasing number of patients and brain tumor types, the manual analyses of Magnetic Resonance Imaging (MRI) images represent a tiring routine and can lead to human errors. In the goal to surpass these problems, an automatic CAD system is needed. We discussed, in this paper, a new model to classify brain tumors using CNN. The suggested scheme is experimentally evaluated on a public dataset. The proposed approach yields a convincing performance compared to previous techniques based on the experimental results.",

keywords = "Classification, CNN, Deep Learning, MRI, Tumor",

author = "Wadhah Ayadi and Wajdi Elhamzi and Mohamed Atri",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 9th IEEE International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022 ; Conference date: 28-05-2022 Through 30-05-2022",

year = "2022",

doi = "10.1109/SETIT54465.2022.9875468",

language = "English",

series = "2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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booktitle = "2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022",

address = "United States",

}

Ayadi, W, Elhamzi, W & Atri, M 2022, Multi-Classification of brain tumor based on deep CNN. in 2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022. 2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022, Institute of Electrical and Electronics Engineers Inc., pp. 87-90, 9th IEEE International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022, Hammamet, Tunisia, 28/05/22. https://doi.org/10.1109/SETIT54465.2022.9875468

Multi-Classification of brain tumor based on deep CNN. / Ayadi, Wadhah; Elhamzi, Wajdi; Atri, Mohamed.
2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 87-90 (2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Multi-Classification of brain tumor based on deep CNN

AU - Ayadi, Wadhah

AU - Elhamzi, Wajdi

AU - Atri, Mohamed

PY - 2022

Y1 - 2022

N2 - In the last decades, brain tumors are considered one of the mortal cancers in the world. The right tumors detection and identification in the early phases have a significant role to select an accurate treatment. Due to the increasing number of patients and brain tumor types, the manual analyses of Magnetic Resonance Imaging (MRI) images represent a tiring routine and can lead to human errors. In the goal to surpass these problems, an automatic CAD system is needed. We discussed, in this paper, a new model to classify brain tumors using CNN. The suggested scheme is experimentally evaluated on a public dataset. The proposed approach yields a convincing performance compared to previous techniques based on the experimental results.

AB - In the last decades, brain tumors are considered one of the mortal cancers in the world. The right tumors detection and identification in the early phases have a significant role to select an accurate treatment. Due to the increasing number of patients and brain tumor types, the manual analyses of Magnetic Resonance Imaging (MRI) images represent a tiring routine and can lead to human errors. In the goal to surpass these problems, an automatic CAD system is needed. We discussed, in this paper, a new model to classify brain tumors using CNN. The suggested scheme is experimentally evaluated on a public dataset. The proposed approach yields a convincing performance compared to previous techniques based on the experimental results.

KW - Classification

KW - CNN

KW - Deep Learning

KW - MRI

KW - Tumor

UR - https://www.scopus.com/pages/publications/85139012653

U2 - 10.1109/SETIT54465.2022.9875468

DO - 10.1109/SETIT54465.2022.9875468

M3 - Conference contribution

AN - SCOPUS:85139012653

T3 - 2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022

SP - 87

EP - 90

BT - 2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 9th IEEE International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022

Y2 - 28 May 2022 through 30 May 2022

ER -

Ayadi W, Elhamzi W, Atri M. Multi-Classification of brain tumor based on deep CNN. In 2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 87-90. (2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022). doi: 10.1109/SETIT54465.2022.9875468

Multi-Classification of brain tumor based on deep CNN

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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