Lung Imaging and Computer Aided Diagnosis
eBook - PDF

Lung Imaging and Computer Aided Diagnosis

  1. 496 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Lung Imaging and Computer Aided Diagnosis

About this book

Lung cancer remains the leading cause of cancer-related deaths worldwide. Early diagnosis can improve the effectiveness of treatment and increase a patient's chances of survival. Thus, there is an urgent need for new technology to diagnose small, malignant lung nodules early as well as large nodules located away from large diameter airways because

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Yes, you can access Lung Imaging and Computer Aided Diagnosis by Ayman El-Baz, Jasjit S. Suri, Ayman El-Baz,Jasjit S. Suri in PDF and/or ePUB format, as well as other popular books in Medicine & Biotechnology in Medicine. We have over one million books available in our catalogue for you to explore.

Information

Publisher
CRC Press
Year
2016
eBook ISBN
9781439845585
Edition
1
Topic
Medicine
Subtopic
Biotechnology in Medicine

Table of contents

  1. Front Cover
  2. Contents
  3. Editors
  4. Contributors
  5. Chapter 1 - A Novel Three-Dimensional Framework for Automatic Lung Segmentation from Low- Dose Computed Tomography Images
  6. Chapter 2 - Incremental Engineering of Lung Segmentation Systems
  7. Chapter 3 - 3D MGRF-Based Appearance Modeling for Robust Segmentation of Pulmonary Nodules in 3D LDCT Chest Images
  8. Chapter 4 - Ground-Glass Nodule Characterization in High- Resolution Computed Tomography Scans
  9. Chapter 5 - Four-Dimensional Computed Tomography Lung Registration Methods
  10. Chapter 6 - Pulmonary Kinematics via Registration of Serial Lung Images
  11. Chapter 7 - Acquisition and Automated Analysis of Normal and Pathological Lungs in Small Animals Using Microcomputed Tomography
  12. Chapter 8 - Airway Segmentation and Analysis from Computed Tomography
  13. Chapter 9 - Pulmonary Vessel Segmentation for Multislice CT Data:: Methods and Applications
  14. Chapter 10 - A Novel Level Set-Based Computer-Aided Detection System for Automatic Detection of Lung Nodules in Low-Dose Chest Computed Tomography Scans
  15. Chapter 11 - Model-Based Methods for Detection of Pulmonary Nodules
  16. Chapter 12 - Concept and Practice of Genetic Algorithm Template Matching and Higher Order Local Autocorrelation Schemes in Automated Detection of Lung Nodules
  17. Chapter 13 - Computer-Aided Detection of Lung Nodules in Chest Radiographs and Thoracic CT
  18. Chapter 14 - Lung Nodule and Tumor Detection and Segmentation
  19. Chapter 15 - Texture Classification in Pulmonary CT
  20. Chapter 16 - Computer-Aided Assessment and Stenting of Tracheal Stenosis
  21. Chapter 17 - Appearance Analysis for the Early Assessment of Detected Lung Nodules
  22. Chapter 18 - Validation of a New Image-Based Approach for the Accurate Estimating of the Growth Rate of Detected Lung Nodules Using Real Computed Tomography Images and Elastic Phantoms Generated by State-of-the-Art Microfluidics Technology
  23. Chapter 19 - Three-Dimensional Shape Analysis Using Spherical Harmonics for Early Assessment of Detected Lung Nodules
  24. Chapter 20 - Review on Computer-Aided Detection, Diagnosis, and Characterization of Pulmonary Nodules: A Clinical Perspective
  25. Back Cover