A deep learning based NeuroFusionNet approach for automated brain tumor diagnosis from MRI
Omara Mustafa, Salem Alhatamleh, Hamad Yahia Abu Mhanna, Abdallah Almahmoud, Rami Malkawi, Majd Malkawi, Abdel-Baset Bani Yaseen, Hanan Fawaz Akhdar, Hatem Malkawi, Fatimah Maashey, Latifah Alghulayqah, Mohammad Amin · 2026
Read A deep learning based NeuroFusionNet approach for automated brain tumor diagnosis from MRI by Omara Mustafa, Salem Alhatamleh, Hamad Yahia Abu Mhanna, Abdallah Almahmoud, Rami Malkawi, Majd Malkawi, Abdel-Baset Bani Yaseen, Hanan Fawaz Akhdar, Hatem Malkawi, Fatimah Maashey, Latifah Alghulayqah, Mohammad Amin (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13131096.txt.
Description
Omara Mustafa and co-authors present a deep learning system that sorts brain tumors from MRI scans in a 2026 paper. Reading such scans by hand is slow, and tumors vary a lot in shape and look. Their system, NeuroFusionNet, first grows the training set with fake scans made by a generative network. A proven image network, VGG16, then reads both real and fake scans, with its last ten layers retuned for MRI while the rest stay frozen.
On two public scan sets, the system reached about ninety-nine percent accuracy on each. It beat five rival designs, among them deeper and mobile nets. The authors credit the mix of extra synthetic data and careful fine-tuning. Tools of this kind could speed first reads in busy clinics.
Catalog record
| CREATOR | Omara Mustafa, Salem Alhatamleh, Hamad Yahia Abu Mhanna, Abdallah Almahmoud, Rami Malkawi, Majd Malkawi, Abdel-Baset Bani Yaseen, Hanan Fawaz Akhdar, Hatem Malkawi, Fatimah Maashey, Latifah Alghulayqah, Mohammad Amin |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 53 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |