Intracranial hemorrhage detection using CNN-LSTM fusion model

Intracranial hemorrhage detection using CNN-LSTM fusion model

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.

Bibliographic Details
Main Authors: Ahmed, Kazi sabab, Shariar, Khandaker Sadab, Naim, Naimul Hasan, Hazari, MD. Nayimur Rahman
Other Authors: Alam, Md. Golam Rabiul
Format: Thesis
Language:English
Published: Brac University 2022
Subjects:
Deep learning
Convolutional neural network (CNN)
Magnetic Resonance Imaging (MRI)
Magnetic Resonance Angiogram (MRA)
Intracranial hemorrhage
Recurrent Neural Network (RNN)
Cognitive learning theory (Deep learning)
Neural networks (Computer science)
Machine learning
Online Access:http://hdl.handle.net/10361/17333

Internet

http://hdl.handle.net/10361/17333

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