Brain Tumor MRI Image Segmentation Using Deep Learning Techniques
eBook - ePub

Brain Tumor MRI Image Segmentation Using Deep Learning Techniques

  1. 258 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Brain Tumor MRI Image Segmentation Using Deep Learning Techniques

About this book

Brain Tumor MRI Image Segmentation Using Deep Learning Techniques offers a description of deep learning approaches used for the segmentation of brain tumors. The book demonstrates core concepts of deep learning algorithms by using diagrams, data tables and examples to illustrate brain tumor segmentation. After introducing basic concepts of deep learning-based brain tumor segmentation, sections cover techniques for modeling, segmentation and properties. A focus is placed on the application of different types of convolutional neural networks, like single path, multi path, fully convolutional network, cascade convolutional neural networks, Long Short-Term Memory - Recurrent Neural Network and Gated Recurrent Units, and more. The book also highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in brain tumor segmentation. - Provides readers with an understanding of deep learning-based approaches in the field of brain tumor segmentation, including preprocessing techniques - Integrates recent advancements in the field, including the transformation of low-resolution brain tumor images into super-resolution images using deep learning-based methods, single path Convolutional Neural Network based brain tumor segmentation, and much more - Includes coverage of Long Short-Term Memory (LSTM) based Recurrent Neural Network (RNN), Gated Recurrent Units (GRU) based Recurrent Neural Network (RNN), Generative Adversarial Networks (GAN), Auto Encoder based brain tumor segmentation, and Ensemble deep learning Model based brain tumor segmentation - Covers research Issues and the future of deep learning-based brain tumor segmentation

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Yes, you can access Brain Tumor MRI Image Segmentation Using Deep Learning Techniques by Jyotismita Chaki in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Biotechnology. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Front Matter
  3. Table of Contents
  4. Front Matter
  5. Copyright
  6. Contents
  7. Contributors
  8. List of Illustrations
  9. List of Tables
  10. 1 : Brain MRI segmentation using deep learning: background study and challenges
  11. 2 : Data preprocessing techniques for MRI brain scans using deep learning models
  12. 3 : A survey of brain segmentation methods from magnetic resonance imaging
  13. 4 : Brain tumor segmentation and detection in magnetic resonance imaging (MRI) using convolutional neural network
  14. 5 : Simultaneous brain tumor segmentation and molecular profiling using deep learning and T2w magnetic resonance images
  15. 6 : An adaptive smart healthcare system to detect tumor from brain MRI using machine learning algorithm
  16. 7 : Deep learningā€“based decision support system for multicerebral disease classification and identification
  17. 8 : Multimodal MRI Brain Tumor Segmentationā€”A ResNet-based U-Net approach
  18. 9 : Deep learning-based brain malignant neoplasm classification using MRI image segmentation assisted by bias field correction and histogram equalization
  19. 10 : Brain MRI segmentation techniques based on CNN and its variants
  20. 11 : Detection of Brain Tumor with Magnetic Resonance Imaging using Deep Learning Techniques
  21. 12 : On comparing optimizer of UNet-VGG16 architecture for brain tumor image segmentation
  22. 13 : Comparative analysis of deformable models based segmentation methods for brain tumor classification
  23. 14 : Brain tumor segmentation using deep learning: taxonomy, survey and challenges
  24. Index
  25. A