Semantic segmentation of tumor from 3D Structural MRI using U-Net Autoencoder
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020.
Principais autores: | Farzana, Maisha, Any, Md. Jahid Hossain |
---|---|
Outros Autores: | Parvez, Mohammad Zavid |
Formato: | Tese |
Idioma: | en_US |
Publicado em: |
Brac University
2021
|
Assuntos: | |
Acesso em linha: | http://hdl.handle.net/10361/14459 |
Registros relacionados
-
In-depth analysis of deep learning architectures for brain tumor classification in MRI scans
por: Haque, Hossain MD. Hasibul, et al.
Publicado em: (2024) -
Brain tumor segmentation from MRI images using convolutional neural networks
por: Khan, Mushfiqur Rahman
Publicado em: (2024) -
Detecting brain tumor using deep neural networks from MRI images
por: Imamuzzaman, A.S.M., et al.
Publicado em: (2021) -
Lossless segmentation of Brain Tumors from MRI images using 3D U-Net
por: Farha, Ramisa, et al.
Publicado em: (2022) -
A comparison of deep learning U‐Net architectures for semantic segmentation on panoramic X-ray images
por: Bin Mushfiq, Rahil, et al.
Publicado em: (2024)