An automated deep learning framework for brain tumor classification using MRI imagery
Abstract The precise and timely diagnosis of brain tumors is essential for accelerating patient recovery and preserving lives. Brain tumors exhibit a variety of sizes, shapes, and visual characteristics, requiring individualized treatment strategies for each patient. Radiologists require considerabl...
Saved in:
| Main Authors: | Muhammad Aamir, Ziaur Rahman, Uzair Aslam Bhatti, Waheed Ahmed Abro, Jameel Ahmed Bhutto, Zhonglin He |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-02209-2 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Automated Vertebral Bone Quality Determination from T1-Weighted Lumbar Spine MRI Data Using a Hybrid Convolutional Neural Network–Transformer Neural Network
by: Kristian Stojšić, et al.
Published: (2024-11-01) -
Automated detection of wrist ganglia in MRI using convolutional neural networks
by: Mathias Hämäläinen, et al.
Published: (2025-08-01) -
An integrated deep convolutional neural networks framework for the automatic segmentation and grading of glioma tumors using multimodal MRI scans
by: Otung John Peter Odong, et al.
Published: (2025-08-01) -
A novel network with enhanced edge information for left atrium segmentation from LGE-MRI
by: Ze Zhang, et al.
Published: (2024-12-01) -
Dye sensitized photocatalytic degradation of congo red and rhodamine B by 1,3,5-Benzenetricarboxylic acid based metal organic frameworks Ni3(BTC)2.12H2O, (Ni0.8Co0.2)3(BTC)2.12H2O and Cu3(BTC)2 under visible light
by: Kavitha Karuppiah, et al.
Published: (2025-03-01)