Rationale And Objectives: The aim of this study was to retrospectively evaluate an automated global scoring system for evaluating the extent and severity of disease in a known cohort of patients with documented bronchiectasis. On the basis of a combination of validated three-dimensional automated algorithms for bronchial tree extraction and quantitative airway measurements, global scoring combines the evaluation of bronchial lumen-to-artery ratios and bronchial wall-to-artery ratios, as well as the detection of mucoid-impacted airways. The result is an automatically generated global computed tomographic (CT) score designed to simplify and standardize the interpretation of scans in patients with chronic airway infections.
View Article and Find Full Text PDFIEEE Trans Med Imaging
October 2009
Automatic extraction of vertebra regions from a spinal magnetic resonance (MR) image is normally required as the first step to an intelligent spinal MR image diagnosis system. In this work, we develop a fully automatic vertebra detection and segmentation system, which consists of three stages; namely, AdaBoost-based vertebra detection, detection refinement via robust curve fitting, and vertebra segmentation by an iterative normalized cut algorithm. In order to produce an efficient and effective vertebra detector, a statistical learning approach based on an improved AdaBoost algorithm is proposed.
View Article and Find Full Text PDFAlthough to date, the major impetus for the development of computer-assisted diagnosis (CAD) has been the detection of pulmonary nodules, CAD should properly be viewed as a potential tool for assisting radiologic interpretation of the entire gamut of chest diseases, including not just enhanced detection of disease but also characterization and quantification, ideally leading to improved patient management. The use of CAD to improve visualization of the airways using advanced computer techniques, including sophisticated methods for obtaining 3-dimensional segmentation of the central airways and, in particular, the development of virtual bronchoscopy has been recently studied. In this paper, the authors review the development of a specific series of CAD applications enabling automated identification and characterization of chronically inflamed airways.
View Article and Find Full Text PDFMed Image Comput Comput Assist Interv
January 2008
Computed tomography (CT) images of the lungs provide high resolution views of the airways. Quantitative measurements such as lumen diameter and wall thickness help diagnose and localize airway diseases, assist in surgical planning, and determine progress of treatment. Automated quantitative analysis of such images is needed due to the number of airways per patient.
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