Comparison of Various Colorization Techniques for MRI Brain Tumor Segmentation using Convolutional Neural Networks-Reference-Cited by-同舟云学术

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Comparison of Various Colorization Techniques for MRI Brain Tumor Segmentation using Convolutional Neural Networks

Published:2023-12-02 Issue: Volume:62 Page:1-6
ISSN:
Container-title:2023 IEEE 8th International Conference on Recent Advances and Innovations in Engineering (ICRAIE)
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Author:

Azam Akmal Shafiq Badarul¹,Jumaat Abdul Kadir²,Ibrahim Shafaf³

Affiliation:

1. Universiti Teknologi MARA,School of Mathematical Sciences, College of Computing, Informatics and Mathematics,Mukah,Malaysia

2. Universiti Teknologi MARA,School of Mathematical Sciences, College of Computing, Informatics and Mathematics, Institute for Big Data Analytics and Artificial Intelligence (IBDAAI),Shah Alam,Selangor,Malaysia

3. Universiti Teknologi MARA,School of Computing Sciences, College of Computing, Informatics and Mathematics,Shah Alam,Selangor,Malaysia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10467192/10468068/10468529.pdf?arnumber=10468529

Reference30 articles.

1. A Systematic Approach for MRI Brain Tumor Localization and Segmentation Using Deep Learning and Active Contouring

2. A Novel Brain Tumor Detection and Coloring Technique from 2D MRI Images

3. Attention U-Net with Active Contour Based Hybrid Loss for Brain Tumor Segmentation

4. A survey of methods for brain tumor segmentation-based MRI images

5. T1w MRI Brain Tumor Image Segmentation using Active Contour Models and Convolution Neural Network Fusion

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