Utilizing Customized 3D U-Net Framework for the Classification and Segmentation of Multi-regional Brain Tumors in Volumetric MRI Images-Reference-Cited by-同舟云学术

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Utilizing Customized 3D U-Net Framework for the Classification and Segmentation of Multi-regional Brain Tumors in Volumetric MRI Images

Published:2024-04-25 Issue: Volume: Page:1-6
ISSN:
Container-title:2024 3rd International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)
language:
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Author:

Titu Md. Minhaj Taher¹,Mary Mekhala Mariam¹,Ahamed Md. Faysal²,Oishee Tasfia Mashud³,Hasan Md Mahadi³

Affiliation:

1. International Standard University,Department of Computer Science & Engineering,Dhaka,Bangladesh,1212

2. Rajshahi University of Engineering & Technology,Department of Electrical & Computer Engineering,Rajshahi,Bangladesh,6204

3. International Standard University,Department of Computer Science and Engineering,Dhaka,Bangladesh,1212

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10561631/10561632/10561700.pdf?arnumber=10561700

Reference19 articles.

1. Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation

2. Brain Tumour Image Segmentation Using Deep Networks

3. HI-Net: Hyperdense Inception 3D UNet for Brain Tumor Segmentation

4. LBTS‐Net: A fast and accurate CNN model for brain tumour segmentation

5. Diagnosis of Brain Tumor Using Light Weight Deep Learning Model with Fine-Tuning Approach

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