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In this paper, we present a fully automatic method to quantify Tree-in-Bud (TIB) patterns for respiratory tract infections. The proposed quantification method is based on our previous effort to detect and track TIB patterns with a computer assisted detection (CAD) system [9]. In addition to accurately identifying TIB on CT, quantifying TIB is important for measuring the volume of affected lung as...
We present an image pipeline for airway phenotype extraction suitable for large-scale genetic and epidemiological studies including genome-wide association studies (GWAS) in Chronic Obstructive Pulmonary Disease (COPD). We use scale-space particles to densely sample intraparenchymal airway locations in a large cohort of high-resolution CT scans. The particle methodology is based on a constrained energy...
Monte Carlo x-ray transport simulation codes can generate radiographic images that are equivalent to images produced by clinical systems. Most codes optimized for medical imaging use voxels to represent the patient anatomy and employ delta scattering (Woodcock algorithm) as an essential acceleration technique. With delta scattering all voxels have the same attenuation and x rays cross multiple voxels...
The differential phase contrast CT (DPC-CT) implemented with x-ray tube and grating is emerging as a new technology to improve the contrast sensitivity of the conventional CT. Via system modeling, analysis and computer simulation, we investigate the DPC-CT's characteristics of signal and noise and compare them with the conventional CT. The preliminary data show that the DPC-CT possesses a modulation...
The locations of lung nodules relative to the other lung anatomical structures are important hints of malignant cancers. In this paper, we propose a fully automatic method to identify if a lung nodule is well-circumscribed, juxta-vascular, juxta-pleural or pleural tail in computed tomography (CT) images. First, we design an optimized graph model, introducing new global and region-based energy terms,...
We present a novel and fast interactive approach to multi-modality cardiac image segmentation, which employs the linearly ordered surfaces as an additional constraint. We show using such a geometrical constraint helps to significantly reduce user interaction and improve the accuracy of segmentation results at the same time. We solve the proposed multiregion segmentation problem with the order constraints...
We propose a novel approach for diagnosing malignant lung nodules based on analyzing the spatial distribution of Hounsfield values for the detected lung nodules. Spatial distribution of image intensities (or Hounsfield values) comprising the malignant nodule appearance is accurately modeled with a new rotationally invariant second-order Markov-Gibbs Random Field (MGRF). In this paper, we introduce...
We present a fully automatic computational vascular morphometry (CVM) approach for the clinical assessment of pulmonary vascular disease (PVD). The approach is based on the automatic extraction of the lung intraparenchymal vasculature using scale-space particles. Based on the detected features, we developed a set of image-based biomarkers for the assessment of the disease using the vessel radii estimation...
Robust initialization is essential for any successful segmentation process of medical images. For CT images, initialization is challenging because quality, appearance, content, and field-of-view of the images are highly variable. Furthermore, high execution speed is desirable, whereas the user tolerance to errors is low in clinical applications. We present a new method for efficient and robust positioning...
In clinical practice, detection and quantification of calcified lesions in the coronary arteries and aorta is normally performed on non contrast enhanced Computed Tomography (CT) scans. This CT scan is generally followed by a contrast enhanced angiography (CTA) scan for better plaque visualization. We propose and evaluate a method for the detection of calcified lesions on CTA scans. Calcium lesion...
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