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A Path along Deep Learning for Medical Image Analysis : With Focus on Burn Wounds and Brain Tumors.

Bibliographic Details
Main Author: Cirillo, Marco Domenico.
Format: eBook
Language:English
Published: Linköping : Linkopings Universitet, 2021.
Edition:1st ed.
Series:Linköping Studies in Science and Technology. Dissertations Series
Subjects:
Electronic books.
Online Access:Click to View
Table of Contents:
  • Intro
  • Abstract
  • Acknowledgments
  • Contents
  • List of Figures
  • Introduction
  • Aim
  • Delimitations
  • Research questions
  • Included papers
  • Research ethics
  • Outline
  • Burn Wounds and Brain Tumors
  • Burn wounds
  • Pathophysiology
  • Assessment methods
  • Brain tumors
  • Pathophysiology
  • Assessment methods
  • Reflections
  • Image Features
  • Type of features
  • Color features
  • Edge feature
  • Texture features
  • Mixed features
  • Principal component analysis
  • Independent component analysis
  • Tensor decomposition
  • Deep features
  • Convolution
  • Deep features
  • Reflections
  • Convolutional Neural Networks
  • Deep learning basics
  • Loss functions
  • Forward and backward propagation
  • Data pre-processing
  • Weight initialization
  • Normalization layers
  • Activation functions
  • Optimization
  • Regularization
  • Residual block
  • Convolutional neural networks
  • Convolutional layers
  • CNNs for image classification
  • CNNs for image segmentation
  • CNNs for image generation
  • Reflections
  • Image Augmentation
  • Image Augmentation Techniques
  • Patch extraction
  • Flipping
  • Rotation
  • Scaling
  • Elastic grid-based deformation
  • Brightness
  • Reflections
  • Generative Adversarial Networks
  • Generator and discriminator
  • GANs in medical imaging
  • GAN losses
  • Image-to-image GANs
  • Pix2Pix
  • Semantic image synthesis with spatially-adaptive normalization
  • Reflections
  • Papers, Discussions and Conclusions
  • Paper I: Tensor decomposition for colour image segmentation of burn wounds
  • Paper II: Time-independent prediction of burn depth using deep convolutional neural networks
  • Paper III: Improving burn depth assessment for pediatric scalds by AI based on semantic segmentation of polarized light photography images
  • Paper IV: Vox2Vox: 3D-GAN for brain tumour segmentation.
  • Paper V: What is the best data augmentation for 3D brain tumor segmentation?
  • Conclusions
  • Bibliography
  • Papers.

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