Landmarking and segmentation of 3D CT images
Segmentation and landmarking of computed tomographic (CT) images of pediatric patients are important and useful in computer-aided diagnosis (CAD), treatment planning, and objective analysis of normal as well as pathological regions. Identification and segmentation of organs and tissues in the presen...
| Main Author: | |
|---|---|
| Other Authors: | , |
| Format: | Electronic |
| Language: | English |
| Published: |
San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) :
Morgan & Claypool Publishers,
c2009.
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| Series: | Synthesis lectures on biomedical engineering (Online),
# 30. |
| Subjects: | |
| Online Access: | Abstract with links to full text |
Table of Contents:
- Introduction to medical image analysis
- Medical diagnostic imaging
- Imaging modalities
- Tissue characterization in CT images
- Computer-aided analysis of medical images
- Knowledge-based segmentation
- Atlas-based segmentation
- Landmarking of medical images
- Objectives and organization of the book
- Image segmentation
- Digital image processing
- Histogram
- Thresholding
- Region-based methods
- Region growing
- Region splitting and merging
- Edge-based techniques
- Active contour modeling
- Mathematical model of deformable contours
- Gradient vector flow
- The Hough transform
- The convex hull
- Fuzzy segmentation
- Fuzzy sets
- Fuzzy mapping
- Fuzzy connectivity
- Morphological image processing
- Binary morphological image processing
- Gray-scale morphological image processing
- Morphological reconstruction
- Segmentation using opening-by-reconstruction
- Remarks
- Experimental design and database
- Experimental design
- CT exams and dataset
- Methods of evaluation of the results
- Qualitative assessment
- Quantitative assessment
- Remarks
- Ribs, vertebral column, and spinal canal
- The vertebral column and the spinal canal
- Removal of peripheral artifacts and tissues
- Removal of the external air
- Removal of the skin
- Removal of the peripheral fat
- Removal of the peripheral muscle
- Identification of the rib structure
- Assessment of the results
- Segmentation of the vertebral column
- Qualitative evaluation of the results
- Quantitative evaluation of the results
- Identification of the spinal canal
- Delimitation of the search range for seed detection
- Detection of seed voxels using the Hough transform
- Extraction of the spinal canal
- Qualitative evaluation of the results
- Quantitative evaluation of the results
- Applications
- Remarks
- Delineation of the diaphragm
- The diaphragm
- Segmentation of the lungs
- Delineation of the diaphragm
- Linear least-squares procedure to model the diaphragm
- Active contour modeling of the diaphragm
- Qualitative assessment of the results
- Quantitative assessment of the results
- Applications
- Remarks
- Delineation of the pelvic girdle
- The pelvic girdle
- Delineation of the pelvic girdle
- Detection of seed voxels in the pelvic girdle
- Segmentation of the pelvic girdle
- Linear least-squares procedure to model the upper pelvic surface
- Active contour modeling of the upper pelvic surface
- Qualitative assessment of the results
- Quantitative assessment of the results
- Applications
- Remarks
- Application of landmarking
- Neuroblastoma
- Computer-aided analysis of neuroblastoma
- Segmentation of neuroblastic tumors
- Analysis of the results
- Qualitative analysis
- Quantitative analysis
- Remarks
- Concluding remarks
- Bibliography.