Automatic brain-tumor diagnosis using cascaded deep convolutional neural networks with symmetric U-Net and asymmetric residual-blocks.
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| Title: | Automatic brain-tumor diagnosis using cascaded deep convolutional neural networks with symmetric U-Net and asymmetric residual-blocks. |
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| Authors: | Abd-Ellah MK; Faculty of Artificial Intelligence, Egyptian Russian University, Cairo, 11829, Egypt. mahmoud-khaled@eru.edu.eg., Awad AI; College of Information Technology, United Arab Emirates University, P.O. Box 15551, Al Ain, United Arab Emirates. ali.awad@uaeu.ac.ae.; Faculty of Engineering, Al-Azhar University, P.O. Box 83513, Qena, Egypt. ali.awad@uaeu.ac.ae., Khalaf AAM; Department of Electrical Engineering, Faculty of Engineering, Minia University, Minia, 61519, Egypt., Ibraheem AM; Faculty of Artificial Intelligence, Egyptian Russian University, Cairo, 11829, Egypt. |
| Source: | Scientific reports [Sci Rep] 2024 Apr 25; Vol. 14 (1), pp. 9501. Date of Electronic Publication: 2024 Apr 25. |
| Publication Type: | Journal Article; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 2045-2322 |
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| DOI: | 10.1038/s41598-024-59566-7 |
