Medical Image Analysis
Description
Key Features
- Provides an authoritative description of key concepts and methods
- Includes tutorial-based sections that clearly explain principles and their application to different medical domains
- Presents a representative selection of topics to match a modern and relevant approach to medical image computing
Readership
Table of Contents
Chapter 1 Historical perspective on Medical Image Analysis
Chapter 2 Brief Introduction to Medical Imaging Modalities
- Comparative synthesis of each technique
- Choosing it where is possible, living with it when not
Chapter 3 Mathematical Preliminaries and Notation
Image Representation
Chapter 4 Image Representation and Filtering
- M: Linear and non-linear filtering
- N: Edge detection and image feature enhancement
Chapter 5 Multi-scale Image Representation
- M: Scale-space theory
- N: Vascular image enhancement
Chapter 6 Multi-resolution Image Representation
- M: Wavelets and other decompositions
- N: Medical image compression
Chapter 7 Multi-dimensional Image Representation
- M: Tensor image representation & analysis
- N: Diffusion tensor imaging
Feature Detection, Analysis and Tracking
Chapter 8 Feature Detection and Texture Analysis
- M: Computer aided diagnosis
- N: Mammographic analysis
Chapter 9 Tracking of Salient Points
- M: Object detection, Kalman filter
- N: Instrument tracking in IR
Image Segmentation
Chapter 10 Clustering-based Segmentation
- M: Voxel-based clustering with bias correction
- N: Brain tissue segmentation
Chapter 11 Statistical Model-based Segmentation
- M: Statistical Shape Models
- N: Cardiac image analysis
Chapter 12 Implicit Model-based Segmentation
- M: PDE-based segmentation
- N: Segmentation of cortical surfaces
Chapter 13 Segmentation of Tree-like Structures
- M: Graph-cut based segmentation
- N: Segmentation of airways and vessels
Image Registration
Chapter 14 Points and Surface Registration
- M: Iterative closest point and variants
- N: Pre-operative to intra-operative mapping
Chapter 15 Graph Matching
- M: Registration of surfaces/trees with imperfect match
- N: Multi-subject registration of brain vasculature
Chapter 16 Volumetric Rigid Registration
- M: Introduce registration metrics and registration error measures
- N: Radiotherapy planning
Chapter 17 Volumetric Non-Rigid Registration
- M: Introduce registration metrics and registration error measures
- N: Construction of population atlases of organs
Chapter 18 Image Mosaicking
- M: Challenges of registration for mosaicking
- N: Endoscopic imaging for colonoscopy or similar
Motion, Deformation and Growth Analysis
Chapter 19 Motion Recovery and Analysis
- M: Optical flow and variants
- N: Motion from cardiac MR tagging
Chapter 20 Deformation Recovery and Analysis
- M: Models of tissue deformation (e.g. sliding deformation)
- N: Respiratory and cardiac motion analysis
Chapter 21 Development, degeneration, and growth analysis
- M: Statistics in Non-Euclidean Spaces: need and rationale
- N: Quantification of brain ageing and tumour growth
Medical Image Analysis in Large Scale Databases
Chapter 22 Detection and counting in large databases
- M: Machine learning methods – part I Bayesian inference
- N: Cell detection and counting in microscopy
Chapter 23 Segmentation and classification
- M: Machine learning methods – part II Deep learning
- N: Cell segmentation and tissue classification in digital pathology
Chapter 24 Population atlases and variability
- M: Manifold learning methods
- N: Atlas of brain development and ageing
Design and Validation of Medical Image Analysis Methods
Chapter 25 Designing Translational Solutions in Medical Image Analysis
- Introduction to the Stanford Biodesign Process
Chapter 26 Assessment of Medical Image Computing Methods
Overview of metrics and validation strategies in medical image computing covering segmentation, registration, learning
Product details
- No. of pages: 934
- Language: English
- Copyright: © Academic Press 2023
- Published: March 17, 2023
- Imprint: Academic Press
- Paperback ISBN: 9780128136577