Back to Search
Start Over
Explainable Convolutional Neural Networks for Brain Cancer Detection and Localisation.
- Source :
-
Sensors (Basel, Switzerland) [Sensors (Basel)] 2023 Sep 02; Vol. 23 (17). Date of Electronic Publication: 2023 Sep 02. - Publication Year :
- 2023
-
Abstract
- Brain cancer is widely recognised as one of the most aggressive types of tumors. In fact, approximately 70% of patients diagnosed with this malignant cancer do not survive. In this paper, we propose a method aimed to detect and localise brain cancer, starting from the analysis of magnetic resonance images. The proposed method exploits deep learning, in particular convolutional neural networks and class activation mapping, in order to provide explainability by highlighting the areas of the medical image related to brain cancer (from the model point of view). We evaluate the proposed method with 3000 magnetic resonances using a free available dataset. The results we obtained are encouraging. We reach an accuracy ranging from 97.83% to 99.67% in brain cancer detection by exploiting four different models: VGG16, ResNet50, Alex_Net, and MobileNet, thus showing the effectiveness of the proposed method.
- Subjects :
- Humans
Neural Networks, Computer
Records
Brain
Brain Neoplasms diagnostic imaging
Subjects
Details
- Language :
- English
- ISSN :
- 1424-8220
- Volume :
- 23
- Issue :
- 17
- Database :
- MEDLINE
- Journal :
- Sensors (Basel, Switzerland)
- Publication Type :
- Academic Journal
- Accession number :
- 37688069
- Full Text :
- https://doi.org/10.3390/s23177614