Highly Accurate Brain Tumor Segmentation and Classification Using Multiple Feature Sets
Purpose: Nowadays, detecting brain tumors is a crucial application. If a tumor is discovered later on, the medical issues are significant. Therefore, early diagnosis is essential. Magnetic Resonance Imaging (MRI) is the most recent detection, diagnosis, and assessment technology. Materials and M...
Saved in:
| Main Authors: | Megha Sunil Borse, Murali Prasad R, Tummala Ranga Babu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Tehran University of Medical Sciences
2025-07-01
|
| Series: | Frontiers in Biomedical Technologies |
| Subjects: | |
| Online Access: | https://fbt.tums.ac.ir/index.php/fbt/article/view/659 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
VSA-GCNN: Attention Guided Graph Neural Networks for Brain Tumor Segmentation and Classification
by: Kambham Pratap Joshi, et al.
Published: (2025-01-01) -
Reducing the dynamic range of infrared images based on block-priority equalization and compression of histograms
by: S. I. Rudikov, et al.
Published: (2022-06-01) -
Texture Analysis and Classification using Local Binary Patterns and Statistical Features
by: Hasan Maher
Published: (2024-09-01) -
A metaheuristic optimization-based approach for accurate prediction and classification of knee osteoarthritis
by: Amal G. Diab, et al.
Published: (2025-05-01) -
The hybrid feature extraction method for classification of adolescence idiopathic scoliosis using Evolving Spiking Neural Network
by: Nurbaity Sabri, et al.
Published: (2022-11-01)