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We propose an automated pipeline for vessel centerline extraction in 3-D computed tomography angiography (CTA) scans with arbitrary fields of view. The principal steps of the pipeline are body part detection, candidate seed selection, segment tracking, which includes centerline extraction, and vessel tree growing. The final tree-growing step can be instantiated in either a semi- or fully automated fashion. The fully automated initialization is carried out using a vessel position regression algorithm. Both semi-and fully automated methods were evaluated on 30 CTA scans comprising neck, abdominal, and leg arteries in multiple fields of view. High detection rates and centerline accuracy values for 38 distinct vessels demonstrate the effectiveness of our approach.
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http://dx.doi.org/10.1109/TMI.2017.2679981 | DOI Listing |
Ann Afr Med
September 2025
Department of Medicine, School of Medicine, Nazarbayev University, Astana, Kazakhstan.
Background: A comprehensive knowledge of renal vasculature is essential to diagnose and carry out safe clinical interventions accurately. Anatomic variations in renal vessels can present procedural challenges in surgeries such as nephrectomy, transplants, and endovascular interventions.
Methods: In the present retrospective study, we analyzed the distribution patterns of the renal vascular variants and measurements of length and diameter in computed tomography angiographies (CTAs).
Jpn J Radiol
September 2025
Department of Radiology, the Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221002, Jiangsu, China.
Background: Stroke, frequently associated with carotid artery disease, is evaluated using carotid computed tomography angiography (CTA). Dual-energy CTA (DE-CTA) enhances imaging quality but presents challenges in maintaining high image clarity with low-dose scans.
Objectives: To compare the image quality of 50 keV virtual monoenergetic images (VMI) generated using Deep Learning Image Reconstruction (DLIR) and Adaptive Statistical Iterative Reconstruction-V (ASIR-V) algorithms under a triple-low scanning protocol in carotid CTA.
Int J Gen Med
September 2025
Department of Radiology, Tangdu Hospital, The Fourth Military Medical University, Xi'an, Shaanxi Province, 710038, People's Republic of China.
Purpose: Compared with retrospective ECG-gated arterial phase scan, to investigate the clinical application value of dual-source CT large-spiral arterial late scan in the imaging evaluation of left atrial appendage (LAA).
Patients And Methods: A total of 108 patients requiring LAA CT angiography (CTA) due to atrial fibrillation (AF) were selected from September 2024 to December 2024, including 52 patients in group A (Flash large-spiral arterial late scan) and 56 patients in group B (retrospective ECG-gated arterial phase scan). All patients underwent double-phase scan.
Radiography (Lond)
September 2025
Department of Radiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, 221002, China; School of Medical Imaging, Xuzhou Medical University, Xuzhou, Jiangsu, 221002, China; Jiangsu Provincial Engineering Research Center for Medical Imaging and Digital Medicine, Xuzhou, Jiangs
Introduction: Carotid artery disease is a major cause of stroke and is frequently evaluated using Carotid CT Angiography (CTA). However, the associated radiation exposure and contrast agent use raise concerns, particularly for high-risk patients. Recent advances in Deep Learning Image Reconstruction (DLIR) offer new potential to enhance image quality under low-dose conditions.
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September 2025
Department of Radiology, University of Colorado School of Medicine/Department of Pediatric Radiology, Children's Hospital Colorado, 13123 East 16th Avenue, Box 125, Aurora, 80045, Colorado, USA.
Background: Previous studies have shown improved image quality in pediatric cardiac imaging using photon-counting detector CT (PCDCT). However, these studies did not evaluate image quality and radiation dose when utilizing the full spectral capabilities of PCDCT scanners. The full spectral capability of PCDCT scanners allows the generation of the entire array of mono-energetic reconstructions, virtual non-contrast (VNC) images, and iodine maps, which have potential advantages in evaluating complex congenital heart disease.
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