Classification of Tumor in Brain MR Images Using Deep Convolutional Neural Network and Global Average Pooling

被引:19
|
作者
Malla, Prince Priya [1 ]
Sahu, Sudhakar [1 ]
Alutaibi, Ahmed I. [2 ]
机构
[1] Kalinga Inst Ind Technol, Sch Elect Engn, Bhubaneswar 751024, India
[2] Majmaah Univ, Coll Comp & Informat Sci, Majmaah 11952, Saudi Arabia
关键词
medical imaging; magnetic resonance imaging; deep learning; transfer learning; tumor detection; global average pooling; SEGMENTATION; CNN;
D O I
10.3390/pr11030679
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Brain tumors can cause serious health complications and lead to death if not detected accurately. Therefore, early-stage detection of brain tumors and accurate classification of types of brain tumors play a major role in diagnosis. Recently, deep convolutional neural network (DCNN) based approaches using brain magnetic resonance imaging (MRI) images have shown excellent performance in detection and classification tasks. However, the accuracy of DCNN architectures depends on the training of data samples since it requires more precise data for better output. Thus, we propose a transfer learning-based DCNN framework to classify brain tumors for example meningioma tumors, glioma tumors, and pituitary tumors. We use a pre-trained DCNN architecture VGGNet which is previously trained on huge datasets and used to transfer its learning parameters to the target dataset. Also, we employ transfer learning aspects such as fine-tune the convolutional network and freeze the layers of the convolutional network for better performance. Further, this proposed approach uses a Global Average Pooling (GAP) layer at the output to avoid overfitting issues and vanishing gradient problems. The proposed architecture is assessed and compared with competing deep learning based brain tumor classification approaches on the Figshare dataset. Our proposed approach produces 98.93% testing accuracy and outperforms the contemporary learning-based approaches.
引用
收藏
页数:17
相关论文
共 50 条
  • [31] A Deep Learning Approach for Brain Tumor Classification and Segmentation Using a Multiscale Convolutional Neural Network
    Diaz-Pernas, Francisco Javier
    Martinez-Zarzuela, Mario
    Anton-Rodriguez, Miriam
    Gonzalez-Ortega, David
    HEALTHCARE, 2021, 9 (02)
  • [32] Classification of Brain Tumours in MRI Images using a Convolutional Neural Network
    Gupta, Isha
    Singh, Swati
    Gupta, Sheifali
    Nayak, Soumya Ranjan
    CURRENT MEDICAL IMAGING, 2023, 20
  • [33] A Deep Adaptive Convolutional Network for Brain Tumor Segmentation from Multimodal MR Images
    Ghosal, Palash
    Reddy, Shanmukha
    Sai, Charan
    Pandey, Vikas
    Chakraborty, Jayasree
    Nandi, Debashis
    PROCEEDINGS OF THE 2019 IEEE REGION 10 CONFERENCE (TENCON 2019): TECHNOLOGY, KNOWLEDGE, AND SOCIETY, 2019, : 1065 - 1070
  • [34] Comparative Analysis of Different Deep Convolutional Neural Network Architectures for Classification of Brain Tumor on Magnetic Resonance Images
    Sachdeva, Jainy
    Sharma, Deepanshu
    Ahuja, Chirag Kamal
    ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING, 2024, 31 (04) : 1959 - 1978
  • [35] Comparative Analysis of Different Deep Convolutional Neural Network Architectures for Classification of Brain Tumor on Magnetic Resonance Images
    Jainy Sachdeva
    Deepanshu Sharma
    Chirag Kamal Ahuja
    Archives of Computational Methods in Engineering, 2024, 31 : 1959 - 1978
  • [36] Brain Tumor Detection using MRI Images and Convolutional Neural Network
    Lamrani, Driss
    Cherradi, Bouchaib
    El Gannour, Oussama
    Bouqentar, Mohammed Amine
    Bahatti, Lhoussain
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2022, 13 (07) : 452 - 460
  • [37] Detection and Classification of Brain Tumors From MRI Images Using a Deep Convolutional Neural Network Approach
    Menaouer, Brahami
    El-Houda, Kebir Nour
    Zoulikha, Dermane
    Mohammed, Sabri
    Matta, Nada
    INTERNATIONAL JOURNAL OF SOFTWARE INNOVATION, 2022, 10 (01)
  • [38] Transfer Learning Using Convolutional Neural Network Architectures for Brain Tumor Classification from MRI Images
    Chelghoum, Rayene
    Ikhlef, Ameur
    Hameurlaine, Amina
    Jacquir, Sabir
    ARTIFICIAL INTELLIGENCE APPLICATIONS AND INNOVATIONS, AIAI 2020, PT I, 2020, 583 : 189 - 200
  • [39] Brain Tumor Detection and Classification Using an Optimized Convolutional Neural Network
    Aamir, Muhammad
    Namoun, Abdallah
    Munir, Sehrish
    Aljohani, Nasser
    Alanazi, Meshari Huwaytim
    Alsahafi, Yaser
    Alotibi, Faris
    DIAGNOSTICS, 2024, 14 (16)
  • [40] Brain Tumor Detection and Classification Using PSO and Convolutional Neural Network
    Ali, Muhammad
    Shah, Jamal Hussain
    Khan, Muhammad Attique
    Alhaisoni, Majed
    Tariq, Usman
    Akram, Tallha
    Kim, Ye Jin
    Chang, Byoungchol
    CMC-COMPUTERS MATERIALS & CONTINUA, 2022, 73 (03): : 4501 - 4518