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Averaging Centerlines: Mean Shift on Paths
[chapter]
2008
Lecture Notes in Computer Science
We show how weighted averaging can be implemented by applying the Mean Shift algorithm to paths, and discuss the details of our implementation. ...
The method has been evaluated on synthetic data, and has been used to generate reference centerlines for evaluation of vessel tracking algorithms. ...
clustering the paths; i) centerlines; j) vessels; k) average path; l) mean shift path. ...
doi:10.1007/978-3-540-85988-8_107
fatcat:cqvdmawkjjgyhbmgcniwcgff2e
Multiscale Centerline Detection
2016
IEEE Transactions on Pattern Analysis and Machine Intelligence
The former tend to become unreliable when the linear structures are very irregular while the latter often has difficulties distinguishing centerline locations from neighboring ones, thus losing accuracy ...
Existing techniques rely either on filters designed to respond to ideal cylindrical structures or on classification techniques. ...
AD is the average distance between ground truth path and centerlines extracted automatically, the smaller the better. ...
doi:10.1109/tpami.2015.2462363
pmid:27295457
fatcat:ltv2unsh2fetda27lvb7lqosei
Cooperative carotid artery centerline extraction in MRI
2018
PLoS ONE
The centerline of the artery bifurcation is often extracted by means of two independent minimum cost paths ranging from the common to the internal and the external carotid artery. ...
This method avoids that both centerlines follow the same cheapest path after the bifurcation, which is a common error when the paths are extracted independently. ...
We define the best path as the one with the lowest average cost, where the total cost is given by the minimal action map U at the end point, which is divided by the path length to get the average cost. ...
doi:10.1371/journal.pone.0197180
pmid:29847545
pmcid:PMC5976187
fatcat:twzyla5wpff6pexbriic4ky3k4
Automatic Road Centerline Extraction from Imagery Using Road GPS Data
2014
Remote Sensing
So there are various methods like geodesic method, SVM, level set, mean shift, shape feature etc. ...
One of the important features of urban areas in urban analysis is the automatic road network extraction. Road extraction can be done by mainly three methods: Manual, automatic, semi-automatic. ...
Jethva, Head of Department in Master's In Information Technology Department, for his valuable knowledge and support and guiding us to the right path. ...
doi:10.3390/rs6099014
fatcat:lpnezxgcmfe6petpqks6benrma
EM-NET: Centerline-Aware Mitochondria Segmentation in EM Images via Hierarchical View-Ensemble Convolutional Network
[article]
2020
arXiv
pre-print
To address these problems, we introduce a multi-task network named EM-Net, which includes an auxiliary centerline detection task to account for shape information of mitochondria represented by centerline ...
To achieve a light-weight 3D network, we introduce a novel hierarchical view-ensemble convolution module to reduce number of parameters, and facilitate multi-view information aggregation.Validations on ...
Minimizing mean squared error L reg between D out and D is utilized to accomplish the centerline detection task. ...
arXiv:1912.00201v3
fatcat:o6r3a32jdbeojeslks27aclmaq
Coronary Centerline Extraction from CCTA Using 3D-UNet
2021
Future Internet
In this paper, we have focused on automated coronary centerline extraction from cardiac computed tomography angiography (CCTA) proposing a 3D version of U-Net architecture, trained with a novel loss function ...
We have obtained promising results for accuracy (between 90–95%) and overlap (between 90–94%) with various network training configurations on the data from the Rotterdam Coronary Artery Centerline Extraction ...
Using this information, a minimal path extractor given a root point can extract the centerline tree. ...
doi:10.3390/fi13040101
fatcat:a54zdoipe5czbn6rrspracnszy
Automatic Extraction of Railroad Centerlines from Mobile Laser Scanning Data
2015
Remote Sensing
In the modeling stage, we present two approaches to determine the centerline location. ...
After that the centerline is implicitly determined by the geometric center of the pair of tracks. ...
Acknowledgments The authors would like to deeply thank Martin Kodde and Rikkert Wienia from Fugro GeoServices not only for providing RAIL-MAP data and reference data, but also for their valuable input on ...
doi:10.3390/rs70505565
fatcat:mz336wiqm5amnilm6hdipdkgwy
Coronary artery centerline extraction in cardiac CT angiography using a CNN-based orientation classifier
2019
Medical Image Analysis
In a third test set containing 36 CCTA scans, fully automatic seeding and centerline extraction led to extraction of on average 92% of clinically relevant coronary artery segments. ...
Extracted centerline points were highly accurate, with an average distance of 0.21 mm to reference centerline points. ...
Minimal cost paths have a high overlap with the reference centerlines, but may suffer from shortcuts between different points on the centerline. ...
doi:10.1016/j.media.2018.10.005
fatcat:ufsipkhfefaf3phk3fzbzbjbwm
Variations in Channel Centerline Migration Rate and Intensity of a Braided Reach in the Lower Yellow River
2021
Remote Sensing
written as a power function of the previous two-year average incoming sediment coefficient or fluvial erosion intensity, and the re [...] ...
Calculated results indicate that: (i) the mean probability of centerline migrating toward the left side was approximately equal to the probability of rightward migration from a long-term sequence; (ii) ...
[19] examined the influence of artificial river regulation projects on lateral migration intensity of mainflow path, and it was found that the mean shifting rate of main-flow path was reduced from 425 ...
doi:10.3390/rs13091680
doaj:abe94af8fa7f4020b63566107c4dbf2b
fatcat:xlchblqbhrgyto2vro6mpy7xcm
MSC-Net: Multitask Learning Network for Retinal Vessel Segmentation and Centerline Extraction
2021
Applied Sciences
Experimental results on different fundus blood vessel datasets (DRIVE, STARE, and CHASE) show that our method can obtain better segmentation and centerline extraction results at different scales and has ...
The clDice loss function is also used to constrain the topological continuity of blood vessel segments and centerline. ...
The methods for comparison, including traditional segmentation methods, are based on matched filters, namely Combination of Shifted Filter Responses (B-COSFIRE) [6] and Weighted Symmetry Filter (WSF) ...
doi:10.3390/app12010403
fatcat:naz2d6nop5fyjmcmufpzsd6b5e
Snake modeling and distance transform approach to vascular centerline extraction and quantification
2003
Computerized Medical Imaging and Graphics
Our method uses the idea of active contour models as well as path planning and distance transforms for the threedimensional centerline extraction of elongated objects such as vessels. ...
The proposed approach is especially efficient for centerline extraction of complex branching structures. ...
These points must ideally be at the centerline of the object, hence, for improved accuracy, the endpoints can be shifted on the surface of the object, in the direction of the gradient field. ...
doi:10.1016/s0895-6111(03)00040-5
pmid:14575785
fatcat:qkbcqlcxlfgd3emwky3jcaqioe
Standardized evaluation methodology and reference database for evaluating coronary artery centerline extraction algorithms
2009
Medical Image Analysis
centerline extraction algorithms, (3) a database containing 32 cardiac CTA datasets with corresponding reference standard is described and made available, and (4) 13 coronary artery centerline extraction ...
Efficiently obtaining a reliable coronary artery centerline from computed tomography angiography data is relevant in clinical practice. ...
The paths of the three observers were combined to one centerline per vessel using a Mean Shift algorithm for open curves: The centerlines are averaged while taking into account the possibly spatially varying ...
doi:10.1016/j.media.2009.06.003
pmid:19632885
pmcid:PMC3843509
fatcat:zakl4k2a6jgf3ezpigkfcxv27a
Accurate Urban Road Centerline Extraction from VHR Imagery via Multiscale Segmentation and Tensor Voting
[article]
2016
arXiv
pre-print
Extensive experiments on two datasets demonstrate that our method achieves higher quantitative results, as well as more satisfactory visual performances by comparing with state-of-the- art methods. ...
This method not only extracts smooth road centerlines, but also connects the discontinuous road centerlines. ...
A fitting based connection algorithm is utilized to complete the road centerline network in the 3 rd stage. adaptive mean shift was used to detect road center points. ...
arXiv:1508.06163v2
fatcat:hqcumr3tcbcu5aznzebhjln27i
Connected component-based technique for automatic extraction of road centerline in high resolution satellite images
2015
EURASIP Journal on Image and Video Processing
The proposed algorithm is implemented on various satellite images, and the results are given in this work. ...
In this paper, a method for automatic extraction of road centerline from high resolution satellite image is proposed. ...
find probability of each pixel being located on the road centerline, and feature points are projected onto ridge lines using the subspace constrained mean shift method. ...
doi:10.1186/s13640-015-0062-9
fatcat:45u2m73qqjcizawgj4dqaomoe4
Lumen segmentation and stenosis quantification of atherosclerotic carotid arteries in CTA utilizing a centerline intensity prior
2013
Medical Physics (Lancaster)
First, centerlines of the internal and external carotid arteries are extracted with an iterative minimum cost path approach in which the costs are based on a measure of medialness and intensity similarity ...
Special effort is made in adding terms based on local centerline intensity prior so as to exclude all possible plaque tissues from the segmentation. ...
The centerline extraction takes on average 10 min; the level set evolution takes on average 15 min; the side branch removal takes around 20 min; the stenosis quantification takes on average 5 s. ...
doi:10.1118/1.4802751
pmid:23635269
fatcat:qi2zyle5tjhl5epcg2y2xt22ti
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