177 results match your criteria centerline extraction


Algorithm of Pulmonary Vascular Segment and Centerline Extraction.

Comput Math Methods Med 2021 25;2021:3859386. Epub 2021 Aug 25.

Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China.

Because pulmonary vascular lesions are harmful to the human body and difficult to detect, computer-assisted diagnosis of pulmonary blood vessels has become the focus and difficulty of the current research. An algorithm of pulmonary vascular segment and centerline extraction which is consistent with the physician's diagnosis process is proposed for the first time. We construct the projection of maximum density, restore the vascular space information, and correct random walk algorithm to satisfy automatic and accurate segmentation of blood vessels. Read More

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Detection of 3D Arterial Centerline Extraction in Spiral CT Coronary Angiography.

J Healthc Eng 2021 21;2021:2670793. Epub 2021 Aug 21.

Changshu Hospital of Chinese Medicine, Changshu 215516, Jiangsu, China.

This paper presents an in-depth study and analysis of the 3D arterial centerline in spiral CT coronary angiography, and constructs its detection and extraction technique. The first time, the distance transform is used to complete the boundary search of the original figure; the second time, the distance transform is used to calculate the value of the distance transform of all voxels, and according to the value of the distance transform, unnecessary voxels are deleted, to complete the initial contraction of the vascular region and reduce the computational consumption in the next process; then, the nonwitnessed voxels are used to construct the maximum inner joint sphere model and find the skeletal voxels that can reflect the shape of the original figure. Finally, the skeletal lines were optimized on these initially extracted skeletal voxels using a dichotomous-like principle to obtain the final coronary artery centerline. Read More

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Technical note: Validation of 3D ultrasound for image registration during oncological liver surgery.

Med Phys 2021 Jul 5. Epub 2021 Jul 5.

Department of Surgical Oncology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek, Amsterdam, The Netherlands.

Purpose: Registration of pre- and intraoperative images is a crucial step of surgical liver navigation, where rigid registration of vessel centerlines is currently commonly used. When using 3D ultrasound (US), accuracy during navigation might be influenced by the size of the intraoperative US volume, yet the relationship between registration accuracy and US volume size is understudied. In this study, we specify an optimal 3D US volume size for registration using varying volumes of liver vasculature. Read More

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Ordered multi-path propagation for vessel centerline extraction.

Phys Med Biol 2021 Jul 19;66(15). Epub 2021 Jul 19.

Laboratory of Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, People's Republic of China.

Vessel centerline extraction from x-ray angiography images is essential for vessel structure analysis in the diagnosis of coronary artery disease. However, complete and continuous centerline extraction remains a challenging task due to image noise, poor contrast, and complexity of vessel structure. Thus, an iterative multi-path search framework for automatic vessel centerline extraction is proposed. Read More

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Automatic Vertebrae Localization and Spine Centerline Extraction in Radiographs of Patients with Adolescent Idiopathic Scoliosis.

Stud Health Technol Inform 2021 May;281:288-292

Swiss Federal Institute of Technology - ETH Zurich, Institute for Biomechanics, Switzerland.

Adolescent Idiopathic Scoliosis (AIS) is lifetime disorder indicated by the abnormal spinal curvature, and it is usually detected in children and adolescents. Traditional radiographic assessment of scoliosis is time-consuming and unreliable due to high variability in images and manual interpretation. Vertebrae localization and centerline extraction from a biplanar X-ray is essential for pathological diagnosis, treatment planning, and decision making. Read More

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Artificial Intelligence to Assist in Exclusion of Coronary Atherosclerosis During CCTA Evaluation of Chest Pain in the Emergency Department: Preparing an Application for Real-world Use.

J Digit Imaging 2021 Jun 31;34(3):554-571. Epub 2021 Mar 31.

Department of Radiology, Ohio State University College of Medicine, Columbus, OH, 43210, USA.

Coronary computed tomography angiography (CCTA) evaluation of chest pain patients in an emergency department (ED) is considered appropriate. While a "negative" CCTA interpretation supports direct patient discharge from an ED, labor-intensive analyses are required, with accuracy in jeopardy from distractions. We describe the development of an artificial intelligence (AI) algorithm and workflow for assisting qualified interpreting physicians in CCTA screening for total absence of coronary atherosclerosis. Read More

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Automatic Aortic Dissection Centerline Extraction Via Morphology-Guided CRN Tracker.

IEEE J Biomed Health Inform 2021 Sep 3;25(9):3473-3485. Epub 2021 Sep 3.

Aortic dissection (AD) centerline extraction has important clinical value in the quantitative diagnosis and treatment of AD disease. However, AD centerline extraction is a difficult task and quantitative evaluation is rarely studied. In this work, we propose a fully automatic algorithm to extract AD centerline based on a convolutional regression network (CRN) and the morphological properties of AD. Read More

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September 2021

Learning-based algorithms for vessel tracking: A review.

Comput Med Imaging Graph 2021 04 30;89:101840. Epub 2021 Jan 30.

School of Data Science, Fudan University, Shanghai, China. Electronic address:

Developing efficient vessel-tracking algorithms is crucial for imaging-based diagnosis and treatment of vascular diseases. Vessel tracking aims to solve recognition problems such as key (seed) point detection, centerline extraction, and vascular segmentation. Extensive image-processing techniques have been developed to overcome the problems of vessel tracking that are mainly attributed to the complex morphologies of vessels and image characteristics of angiography. Read More

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Joint Extraction of Retinal Vessels and Centerlines Based on Deep Semantics and Multi-Scaled Cross-Task Aggregation.

IEEE J Biomed Health Inform 2021 07 27;25(7):2722-2732. Epub 2021 Jul 27.

Retinal vessel segmentation and centerline extraction are crucial steps in building a computer-aided diagnosis system on retinal images. Previous works treat them as two isolated tasks, while ignoring their tight association. In this paper, we propose a deep semantics and multi-scaled cross-task aggregation network that takes advantage of the association to jointly improve their performances. Read More

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Geometrical changes in Anaconda endograft limbs after endovascular aneurysm repair: A potential predictor for limb occlusion.

Semin Vasc Surg 2020 Mar 13;32(3-4):94-105. Epub 2019 Nov 13.

Department of Vascular Surgery, Medisch Spectrum Twente, Enschede, The Netherlands; Multimodality Medical Imaging M3i Group, Faculty of Science and Technology, Technical Medical Centre, University of Twente, PO Box 217, 7500 AE Enschede, The Netherlands; Robotics and Mechatronics Group, Faculty of Electrical Engineering, Mathematics and Computer Science, Technical Medicine Centre, University of Twente, Enschede, The Netherlands.

The emergence of limb occlusion after endovascular aneurysm repair may be related to the conformational changes between the endograft structure and the patient's anatomy. This study analyzed detailed geometric changes of Anaconda endograft (Terumo Aortic, Inchinnan, Scotland, UK) limbs during the cardiac cycle-based computed tomography on serial imaging after graft implantation. Fifteen patients (mean age 72. Read More

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Vesicle transport and growth dynamics in Aspergillus niger: Microscale modeling of secretory vesicle flow and centerline extraction from confocal fluorescent data.

Biotechnol Bioeng 2020 09 27;117(9):2875-2886. Epub 2020 Jun 27.

Chair of Measurement and Control, Technische Universität Berlin, Berlin, Germany.

In this paper, we present a mathematical model to describe filamentous fungal growth based on intracellular secretory vesicles (SVs), which transport cell wall components to the hyphal tip. Vesicular transport inside elongating hyphae is modeled as an advection-diffusion-reaction equation with a moving boundary, transformed into fixed coordinates, and discretized using a high-order weighted essentially nonoscillatory discretization scheme. The model describes the production and the consumption of SVs with kinetic functions. Read More

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September 2020

Fully Automated Segmentation and Shape Analysis of the Thoracic Aorta in Non-contrast-enhanced Magnetic Resonance Images of the German National Cohort Study.

J Thorac Imaging 2020 Nov;35(6):389-398

Department for Diagnostic and Interventional Radiology, University Hospital Tuebingen, Tuebingen.

Purpose: The purpose of this study was to develop and validate a deep learning-based framework for automated segmentation and vessel shape analysis on non-contrast-enhanced magnetic resonance (MR) data of the thoracic aorta within the German National Cohort (GNC) MR study.

Materials And Methods: One hundred data sets acquired in the GNC MR study were included (56 men, average age 53 y [22 to 72 y]). All participants had undergone non-contrast-enhanced MR imaging of the thoracic vessels. Read More

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November 2020

A novel algorithm for refining cerebral vascular measurements in infants and adults.

J Neurosci Methods 2020 07 25;340:108751. Epub 2020 Apr 25.

University of Washington, Box 358050, 850 Republican St, Rm 127, Seattle, WA, 98109-4714, United States. Electronic address:

Background: Comprehensive quantification of intracranial vascular characteristics by vascular tracing provides an objective clinical assessment of vascular structure. However, weak signal or low contrast in small distal arteries, artifacts due to volitional motion, and vascular pulsation are challenges for accurate vessel tracing from 3D time-of-flight (3D-TOF) magnetic resonance angiography (MRA) images.

New Method: A vascular measurement refinement algorithm is developed and validated for robust quantification of intracranial vasculature from 3D-TOF MRA. Read More

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An Effective Retinal Blood Vessel Segmentation by Using Automatic Random Walks Based on Centerline Extraction.

Biomed Res Int 2020 21;2020:7352129. Epub 2020 Mar 21.

College of Computer and Control Engineering, Minjiang University, Fuzhou 350121, China.

The retinal blood vessel analysis has been widely used in the diagnoses of diseases by ophthalmologists. According to the complex morphological characteristics of the blood vessels in normal and abnormal images, an automatic method by using the random walk algorithms based on the centerlines is proposed to segment retinal blood vessels. Hessian-based multiscale vascular enhancement filtering is used to display the vessel structures in maximum intensity projection. Read More

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January 2021

Optimal path generation in scala tympani and path planning for robotic cochlear implant of perimodiolar electrode.

Proc Inst Mech Eng H 2020 Jun 18;234(6):578-589. Epub 2020 Mar 18.

China Jiliang University, Hangzhou, China.

In this study, a new idea of the optimal path generation method was proposed and a path planning strategy for robotic cochlear implant of perimodiolar electrode was designed. The centerline of scala tympani channel was taken as the optimal implant path of the perimodiolar electrode, which aimed to reduce the damage of the electrode to the cochlea during implantation. First, the three-dimensional cochlear model was reconstructed based on the micro-computed tomography images of cochlea, and it was re-segmented to obtain the cross sections of the scala tympani at different angles. Read More

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RiMARS: An automated river morphodynamics analysis method based on remote sensing multispectral datasets.

Sci Total Environ 2020 Jun 15;719:137336. Epub 2020 Feb 15.

Water, Energy and Environmental Engineering Research Unit, University of Oulu, Oulu, Finland.

Assessment and monitoring of river morphology own an important role in river engineering; since, changes in river morphology including erosion and sedimentation affect river cross-sections and flow processes. An approach for River Morphodynamics Analysis based on Remote Sensing (RiMARS) was developed and tested on the case of Mollasadra dam construction on the Kor River, Iran. Landsat multispectral images obtained from the open USGS dataset are used to extract river morphology dynamics by the Modified Normalized Difference Water Index (MNDWI). Read More

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Artery-venous classification in fluorescein angiograms based on region growing with sequential and structural features.

Comput Methods Programs Biomed 2020 Jul 23;190:105340. Epub 2020 Jan 23.

Central South University, the Second Xiangya Hospital, Department of Ophthalmology, Changsha, Hunan Province, 410011, China. Electronic address:

Background And Objectives: Fluorescein angiography (FA) is widely used in ophthalmology for examining retinal hemodynamics and vascular morphology. Artery-venous classification is an important step in FA image processing for measurement of feature parameters, such as arterio-venous passage time (AVP) and arterio-venous width ratio (AVR) that are proven useful in clinical assessment of circulation disturbance and vessel abnormalities. However, manual artery-venous classification needs expertise and is rather time consuming, and little effort has been devoted to develop automatic classification methods. Read More

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Visible Vessels of Vocal Folds: Can they have a Diagnostic Role?

Curr Med Imaging Rev 2019;15(8):785-795

Otorhinolaryngology Department, Faculty of Medicine, Okan University, Istanbul, Turkey.

Background: Challenges in visual identification of laryngeal disorders lead researchers to investigate new opportunities to help clinical examination. This paper presents an efficient and simple method which extracts and assesses blood vessels on vocal fold tissue in order to serve medical diagnosis.

Methods: The proposed vessel segmentation approach has been designed in order to overcome difficulties raised by design specifications of videolaryngostroboscopy and anatomic structure of vocal fold vasculature. Read More

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October 2020

A novel method to model hepatic vascular network using vessel segmentation, thinning, and completion.

Med Biol Eng Comput 2020 Apr 18;58(4):709-724. Epub 2020 Jan 18.

School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, 100083, China.

The accurate modeling of the liver vessel network structure is an important prerequisite for developing a preoperative plan for the liver. Considering that extracting liver blood vessels from patient's abdominal computed tomography(CT) images requires several manual operations, this study proposed an automatic segmentation method of liver vessels based on graph cut, thinning, and vascular combination, which can obtain a complete liver vascular network. First, the CT image was preprocessed by grayscale mapping based on sigmoid function, vessel enhancement based on Hessian filter, and denoising based on anisotropic filter to enhance the grayscale contrast between the vascular and non-vascular parts of the liver. Read More

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Automated Artery Localization and Vessel Wall Segmentation using Tracklet Refinement and Polar Conversion.

IEEE Access 2020 25;8:217603-217614. Epub 2020 Nov 25.

Department of Radiology, University of Washington, Seattle, WA, 98195, USA.

Quantitative analysis of blood vessel wall structures is important to study atherosclerotic diseases and assess cardiovascular event risks. To achieve this, accurate identification of vessel luminal and outer wall contours is needed. Computer-assisted tools exist, but manual preprocessing steps, such as region of interest identification and/or boundary initialization, are still needed. Read More

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November 2020

Optimization design of magnetic filter for the prototype RF negative ion source at ASIPP.

Rev Sci Instrum 2019 Nov;90(11):115117

Institute of Plasma Physics, Chinese Academy of Science, Hefei 230031, People's Republic of China.

For a prestudy of the key science and technology of the RF negative ion source for fusion application, a negative RF ion source test facility was developed at the Institute of Plasma Physics, Chinese Academy of Science (ASIPP). The magnetic filter field in front of the extraction system plays an important role in reducing the loss of negative hydrogen ions and inhibiting coextraction of electrons. The existing filter field of the prototype ion source is generated by permanent magnets arranged on both sides of the expansion chamber; the gradient and the uniformity of the field are poor, resulting in a large plasma distribution unevenness in the experiment. Read More

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November 2019

An automatic evaluation method for retinal image registration based on similar vessel structure matching.

Med Biol Eng Comput 2020 Jan 21;58(1):117-129. Epub 2019 Nov 21.

School of Information and Electronics, Beijing Institute of Technology, No. 5 South Zhong Guan Cun Street, Haidian District, Beijing, 100081, China.

Registration of retinal images is significant for clinical diagnosis. Numerous methods have been proposed to evaluate registration performance. The available evaluation methods can work well in normal image pairs, but fair evaluation cannot be obtained for image pairs with anatomical changes. Read More

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January 2020

Ex vivo evaluation of an atherosclerotic human coronary artery via histology and high-resolution hard X-ray tomography.

Sci Rep 2019 10 4;9(1):14348. Epub 2019 Oct 4.

Biomaterials Science Center, Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland.

Atherosclerotic arteries exhibit characteristic constrictions and substantial deviations from cylindrical shape. Therefore, determining the artery's cross-section along the centerline is challenging, although high-resolution isotropic three-dimensional data are available. Herein, we apply high-resolution computed tomography in absorption and phase to a plaque-containing human artery post-mortem, through the course of the preparation stages for histology. Read More

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October 2019

Artery-vein segmentation in fundus images using a fully convolutional network.

Comput Med Imaging Graph 2019 09 15;76:101636. Epub 2019 Jun 15.

ESAT-PSI, KU Leuven, Kasteelpark Arenberg 10, 3001 Leuven, Belgium.

Epidemiological studies demonstrate that dimensions of retinal vessels change with ocular diseases, coronary heart disease and stroke. Different metrics have been described to quantify these changes in fundus images, with arteriolar and venular calibers among the most widely used. The analysis often includes a manual procedure during which a trained grader differentiates between arterioles and venules. Read More

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September 2019

Automated 3D segmentation and diameter measurement of the thoracic aorta on non-contrast enhanced CT.

Eur Radiol 2019 Sep 23;29(9):4613-4623. Epub 2019 Jan 23.

Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus MC, Rotterdam, The Netherlands.

Objectives: To develop and evaluate a fully automatic method to measure diameters of the ascending and descending aorta on non-ECG-gated, non-contrast computed tomography (CT) scans.

Material And Methods: The method combines multi-atlas registration to obtain seed points, aorta centerline extraction, and an optimal surface segmentation approach to extract the aorta surface around the centerline. From the extracted 3D aorta segmentation, the diameter of the ascending and descending aorta was calculated at cross-sectional slices perpendicular to the extracted centerline, at the level of the pulmonary artery bifurcation, and at 1-cm intervals up to 3 cm above and below this level. Read More

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September 2019

Semi-Automated Extraction of Crohns Disease MR Imaging Markers using a 3D Residual CNN with Distance Prior.

Deep Learn Med Image Anal Multimodal Learn Clin Decis Support (2018) 2018 Sep 20;11045:218-226. Epub 2018 Sep 20.

Boston Children's Hospital and Harvard Medical School.

We propose a 3D residual convolutional neural network (CNN) algorithm with an integrated distance prior for segmenting the small bowel lumen and wall to enable extraction of pediatric Crohns disease (pCD) imaging markers from T1-weighted contrast-enhanced MR images. Our proposed segmentation framework enables, for the first time, to quantitatively assess luminal narrowing and dilation in CD aimed at optimizing surgical decisions as well as analyzing bowel wall thickness and tissue enhancement for assessment of response to therapy. Given seed points along the bowel lumen, the proposed algorithm automatically extracts 3D image patches centered on these points and a distance map from the interpolated centerline. Read More

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September 2018

Coronary artery centerline extraction in cardiac CT angiography using a CNN-based orientation classifier.

Med Image Anal 2019 01 22;51:46-60. Epub 2018 Oct 22.

Image Sciences Institute, University Medical Center Utrecht & Utrecht University, Q.02.4.45, 3508, GA, Utrecht, P.O. Box 85500, The Netherlands. Electronic address:

Coronary artery centerline extraction in cardiac CT angiography (CCTA) images is a prerequisite for evaluation of stenoses and atherosclerotic plaque. In this work, we propose an algorithm that extracts coronary artery centerlines in CCTA using a convolutional neural network (CNN). In the proposed method, a 3D dilated CNN is trained to predict the most likely direction and radius of an artery at any given point in a CCTA image based on a local image patch. Read More

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January 2019

Automatic estimation of the aortic lumen geometry by ellipse tracking.

Int J Comput Assist Radiol Surg 2019 Feb 22;14(2):345-355. Epub 2018 Sep 22.

Complejo Hospitalario Universitario de Santiago (CHUS), Santiago de Compostela, Spain.

Purpose: The shape and size of the aortic lumen can be associated with several aortic diseases. Automated computer segmentation can provide a mechanism for extracting the main features of the aorta that may be used as a diagnostic aid for physicians. This article presents a new fully automated algorithm to extract the aorta geometry for either normal (with and without contrast) or abnormal computed tomography (CT) cases. Read More

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February 2019

Semiautomatic neck curve reconstruction for intracranial aneurysm rupture risk assessment based on morphological parameters.

Int J Comput Assist Radiol Surg 2018 Nov 29;13(11):1781-1793. Epub 2018 Aug 29.

Department of Neuroradiology, University Hospital of Magdeburg, Magdeburg, Germany.

Purpose: Morphological parameters of intracranial aneurysms (IAs) are well established for rupture risk assessment. However, a manual measurement is error-prone, not reproducible and cumbersome. For an automatic extraction of morphological parameters, a 3D neck curve reconstruction approach to delineate the aneurysm from the parent vessel is required. Read More

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November 2018

Automatic Extraction of the Centerline of Corpus Callosum from Segmented Mid-Sagittal MR Images.

Comput Math Methods Med 2018 4;2018:4014213. Epub 2018 Jul 4.

Department of Neurosurgery, The First Affiliated Hospital of Harbin Medical University, Harbin 150001, China.

The centerline, as a simple and compact representation of object shape, has been used to analyze variations of the human callosal shape. However, automatic extraction of the callosal centerline remains a sophisticated problem. In this paper, we propose a method of automatic extraction of the callosal centerline from segmented mid-sagittal magnetic resonance (MR) images. Read More

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December 2018