Institutul de Matematică şi Informatică "Vladimir Andrunachievici"
Universitatea de Stat din MoldovaRO EN
Effective diagnosis of brain tumor classification by using novel DCNN
Authors: Ilyas Fakhir, Zeeshan Khalil, Awais Qasim, Umair Khalil
Keywords: Brain Tumor, Diagnosis, Deep Convolutional Neural Network (DCNN), Medical Imaging Automation, Transfer Learning Models.
– 1.81 Mb
Keywords: Brain Tumor, Diagnosis, Deep Convolutional Neural Network (DCNN), Medical Imaging Automation, Transfer Learning Models.
Abstract
Brain tumors are the most grave and intricate diseases to be diagnosed and treated. In this study, a novel DCNN architecture is proposed. It has an end-to-end learning framework that automatically detects and refines relevant features directly from MRI images. The model will be trained and evaluated on a large-scale brain tumor MRI dataset that comprises SARTAJ, FIGSHARE, and BraTS datasets, which are the most widely used US brain tumor MRI datasets. In order to provide a fair and accurate performance evaluation, several transfer learning models and the concatenation of models will be utilized. The proposed DCNN outperforms pretrained models.1 Department of Computer Science, Government College University,
Lahore, Pakistan
2 Department of Computer Science, University of Management and Technology,
Lahore, Pakistan
Ilyas Fakhir
ORCID: https://orcid.org/0000-0002-3272-616X
E-mail:
Zeeshan Khalil
ORCID: https://orcid.org/0009-0009-4691-0724
E-mail:
Awais Qasim
ORCID: https://orcid.org/0000-0001-8677-9569
E-mail:
Umair Khalil
ORCID: https://orcid.org/0009-0000-2586-7784
E-mail:
Lahore, Pakistan
2 Department of Computer Science, University of Management and Technology,
Lahore, Pakistan
Ilyas Fakhir
ORCID: https://orcid.org/0000-0002-3272-616X
E-mail:
Zeeshan Khalil
ORCID: https://orcid.org/0009-0009-4691-0724
E-mail:
Awais Qasim
ORCID: https://orcid.org/0000-0001-8677-9569
E-mail:
Umair Khalil
ORCID: https://orcid.org/0009-0000-2586-7784
E-mail:
DOI
https://doi.org/10.56415/csjm.v33.15Fulltext
– 1.81 Mb
Contents
- The 3X2A Strategy for Societal Adaptation in the GenAI Era: A Framework for Human-AI Synergy
- Effective diagnosis of brain tumor classification by using novel DCNN
- Improving Anomaly Detection in the HDFS Dataset with Novel Machine Learning Models and Techniques
- Addressing the limitations related to thresholds in scoring-based decision support tools through graphical visualisation
- Enhanced Botnet Detection and Neutralization through Machine Learning: A Synergistic Analysis of Host Activity, Network Patterns with Explainable Insights
- Optimal size of data packets in computer networks
- Visualizing Type-Checking Proofs: An Educational Web-Based System for an Extended Simply Typed Lambda Calculus
