Content: Front Cover; Contents; Editors; Contributors; Chapter 1 --
A Novel Three-Dimensional Framework for Automatic Lung Segmentation from Low- Dose Computed Tomography Images; Chapter 2 --
Incremental Engineering of Lung Segmentation Systems; Chapter 3 --
3D MGRF-Based Appearance Modeling for Robust Segmentation of Pulmonary Nodules in 3D LDCT Chest Images; Chapter 4 --
Ground-Glass Nodule Characterization in High- Resolution Computed Tomography Scans; Chapter 5 --
Four-Dimensional Computed Tomography Lung Registration Methods; Chapter 6 --
Pulmonary Kinematics via Registration of Serial Lung Images. Chapter 7 --
Acquisition and Automated Analysis of Normal and Pathological Lungs in Small Animals Using Microcomputed TomographyChapter 8 --
Airway Segmentation and Analysis from Computed Tomography; Chapter 9 --
Pulmonary Vessel Segmentation for Multislice CT Data:: Methods and Applications; Chapter 10 --
A Novel Level Set-Based Computer-Aided Detection System for Automatic Detection of Lung Nodules in Low-Dose Chest Computed Tomography Scans; Chapter 11 --
Model-Based Methods for Detection of Pulmonary Nodules. Chapter 12 --
Concept and Practice of Genetic Algorithm Template Matching and Higher Order Local Autocorrelation Schemes in Automated Detection of Lung NodulesChapter 13 --
Computer-Aided Detection of Lung Nodules in Chest Radiographs and Thoracic CT; Chapter 14 --
Lung Nodule and Tumor Detection and Segmentation; Chapter 15 --
Texture Classification in Pulmonary CT; Chapter 16 --
Computer-Aided Assessment and Stenting of Tracheal Stenosis; Chapter 17 --
Appearance Analysis for the Early Assessment of Detected Lung Nodules. 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 TechnologyChapter 19 --
Three-Dimensional Shape Analysis Using Spherical Harmonics for Early Assessment of Detected Lung Nodules; Chapter 20 --
Review on Computer-Aided Detection, Diagnosis, and Characterization of Pulmonary Nodules: A Clinical Perspective; Back Cover.
Abstract: 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 the current technology--namely, needle biopsy and bronchoscopy--fail to diagnose those cases. However, the analysis of small, indeterminate lung masses is fraught with many technical difficulties. Often patients must be followed for years with serial