In-depth analysis of deep learning architectures for brain tumor classification in MRI scans
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.
Egile Nagusiak: | Haque, Hossain MD. Hasibul, Apon, MD. Sayeed Arefin, Chowdhury, Dhrubo Rashid, Imtiaz, Shahriar Islam, Mahi, Nishat Tasnim |
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Beste egile batzuk: | Karim, Dewan Ziaul |
Formatua: | Thesis |
Hizkuntza: | English |
Argitaratua: |
Brac University
2024
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Gaiak: | |
Sarrera elektronikoa: | http://hdl.handle.net/10361/24166 |
Antzeko izenburuak
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A review on the occurrence of brain tumor in adults and pediatrics and the associated risk factors
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An efficient ML approach to detect brain tumor using MRI images
nork: Muktadir, MD. Arafat, et al.
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Semantic segmentation of tumor from 3D Structural MRI using U-Net Autoencoder
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Enhancing multiclass brain tumor classification using deep learning: leveraging superior imaging representations to improve inferior modality performance
nork: Hossain, Shah Md. Shakhawath, et al.
Argitaratua: (2024)