21.10.6.4 Medical Applications -- Coronary Arteries, Carotid Arteries

Chapter Contents (Back)
Coronary Artery. Coronary Vessels. Carotid Artery. Blood Vessels.
See also Medical Applications -- Aorta, Aortic Analysis.

CoronARe: A Coronary Artery Reconstruction Challenge,
2017. Dataset, Angiography.
WWW Link. 3D Reconstrucion challange dataset.

Coppini, G., Demi, M., Poli, R., Valli, G.,
An artificial vision system for X-ray images of human coronary trees,
PAMI(15), No. 2, February 1993, pp. 156-162.
IEEE DOI 0401
BibRef

Ruan, S., Bruno, A., Coatrieux, J.L.,
3-Dimensional Motion and Reconstruction of Coronary-Arteries from Biplane Cineangiography,
IVC(12), No. 10, December 1994, pp. 683-689.
Elsevier DOI BibRef 9412

Chen, S.Y.J., Carroll, J.D.,
3-D reconstruction of coronary arterial tree to optimize angiographic visualization,
MedImg(19), No. 4, April 2000, pp. 318-336.
IEEE Top Reference. 0110
BibRef

Chen, S.Y.J., Carroll, J.D., Messenger, J.C.,
Quantitative analysis of reconstructed 3-d coronary arterial tree and intracoronary devices,
MedImg(21), No. 7, July 2002, pp. 724-740.
IEEE Top Reference. 0210
BibRef

Chen, S.Y.J., Carroll, J.D.,
Kinematic and deformation analysis of 4-D coronary arterial trees reconstructed from cine angiograms,
MedImg(22), No. 6, June 2003, pp. 710-721.
IEEE Abstract. 0308
BibRef

Dorsaz, P.A., Dorsaz, L., Doriot, P.A.,
The effect of image distortion on 3-D reconstruction of coronary bypass grafts from angiographic views,
MedImg(19), No. 7, July 2000, pp. 759-762.
IEEE Top Reference. 0110
BibRef

Greenspan, H., Laifenfeld, M., Einav, S., Barnea, O.,
Evaluation of center-line extraction algorithms in quantitative coronary angiography,
MedImg(20), No. 9, September 2001, pp. 928-941.
IEEE Top Reference. 0110
BibRef

Kayikcioglu, T.[Temel], Gangal, A.[Ali], Turhal, M.[Mehmet], Kose, C.[Cemal],
A surface-based method for detection of coronary vessel boundaries in poor quality X-ray angiogram images,
PRL(23), No. 7, May 2002, pp. 783-802.
Elsevier DOI 0203
BibRef

Haraguchi, R.[Ryo], Sugimoto, N.[Naozo], Eiho, S.[Shigeru], Ishida, Y.[Yoshio],
Three Dimensional Reconstruction of Coronary Arteries by Using Registration and Texture-mapping onto Epicardial Surface on Nuclear 3d Image,
IJIG(3), No. 4, October 2003, pp. 567-587. 0310
BibRef

Luo, Z.C.[Zhong-Chi], Wang, Y.Y.[Yuan-Yuan], Wang, W.Q.[Wei-Qi],
Estimating coronary artery lumen area with optimization-based contour detection,
MedImg(22), No. 4, April 2003, pp. 564-566.
IEEE Abstract. 0306
BibRef

Barratt, D.C., Ariff, B.B., Humphries, K.N., Thom, S.A.M.G., Hughes, A.D.,
Reconstruction and quantification of the carotid artery bifurcation from 3-D ultrasound images,
MedImg(23), No. 5, May 2004, pp. 567-583.
IEEE Abstract. 0406
BibRef

Wahle, A., Olszewski, M.E., Sonka, M.,
Interactive Virtual Endoscopy in Coronary Arteries Based on Multimodality Fusion,
MedImg(23), No. 11, November 2004, pp. 1391-1403.
IEEE Abstract. 0411
BibRef

Blondel, C.[Christophe], Malandain, G.[Grégoire], Vaillant, R.[Régis], Ayache, N.J.[Nicholas J.],
Reconstruction of Coronary Arteries From a Single Rotational X-Ray Projection Sequence,
MedImg(25), No. 5, May 2006, pp. 653-663.
IEEE DOI 0605
BibRef
Earlier:
Reconstruction of Coronary Arteries from One Rotational X-Ray Projection Sequence,
INRIARR-5214, 2004.
HTML Version. BibRef

Perrenot, B., Vaillant, R., Prost, R., Finet, G., Douek, P., Peyrin, F.,
Motion Correction for Coronary Stent Reconstruction From Rotational X-ray Projection Sequences,
MedImg(26), No. 10, October 2007, pp. 1412-1423.
IEEE DOI 0711
BibRef

Santhiyakumari, N., Madheswaran, M.,
Non-invasive evaluation of carotid artery wall thickness using improved dynamic programming technique,
SIViP(2), No. 2, June 2008, pp. xx-yy.
Springer DOI 0711
BibRef

Yang, J., Wang, Y., Liu, Y., Tang, S., Chen, W.,
Novel Approach for 3-D Reconstruction of Coronary Arteries From Two Uncalibrated Angiographic Images,
IP(18), No. 7, July 2009, pp. 1563-1572.
IEEE DOI 0906
BibRef

Hernandez-Sabate, A., Gil, D., Fernandez-Nofrerias, E., Radeva, P.I., Marti, E.,
Approaching Artery Rigid Dynamics in IVUS,
MedImg(28), No. 11, November 2009, pp. 1670-1680.
IEEE DOI 0911
BibRef

Gil, D.[Debora], Radeva, P.I.[Petia I.], Saludes, J.,
Segmentation of Artery Wall in Coronary IVUS Images: A Probabilistic Approach,
ICPR00(Vol IV: 352-355).
IEEE DOI 0009
BibRef

Provost, J., Lee, W.N., Fujikura, K., Konofagou, E.E.,
Electromechanical Wave Imaging of Normal and Ischemic Hearts In Vivo,
MedImg(29), No. 3, March 2010, pp. 625-635.
IEEE DOI 1003
BibRef

Schaap, M.[Michiel], van Walsum, T.[Theo], Neefjes, L.A.[Lisan A.], Metz, C.T.[Coert T.], Capuano, E.[Ermanno], de Bruijne, M.[Marleen], Niessen, W.J.[Wiro J.],
Robust Shape Regression for Supervised Vessel Segmentation and its Application to Coronary Segmentation in CTA,
MedImg(30), No. 11, November 2011, pp. 1974-1986.
IEEE DOI 1111
BibRef

Rivest-Henault, D., Sundar, H., Cheriet, M.,
Nonrigid 2D/3D Registration of Coronary Artery Models With Live Fluoroscopy for Guidance of Cardiac Interventions,
MedImg(31), No. 8, August 2012, pp. 1557-1572.
IEEE DOI 1208
BibRef

Zheng, S.[Sheng], Yang, C.[Changcai], Kaptein, B.L.[Bart L.], Hendriks, E.A.[Emile A.], Koning, O.H.J.[Olivier H.J.], Lei, B.J.[Bang-Jun],
Support value based stent-graft marker detection,
PR(46), No. 3, March 2013, pp. 962-975.
Elsevier DOI 1212
Directional support value transform (SVT); Support value matrix; Multiscale correlations; Fluoroscopic roentgenographic stereophotogrammetric analysis (FRSA); Stent-graft markers detection BibRef

Aswathy, M.A., Santha, S, Jayanthi, K.B.,
Analysis of the performance of various algorithms for the segmentation of the carotid artery,
IMVIP12(133-136).
IEEE DOI 1302
BibRef

Baka, N., Metz, C.T., Schultz, C.J., van Geuns, R.J., Niessen, W.J., van Walsum, T.,
Oriented Gaussian Mixture Models for Nonrigid 2D/3D Coronary Artery Registration,
MedImg(33), No. 5, May 2014, pp. 1023-1034.
IEEE DOI 1405
Arteries BibRef

Sifakis, E.G., Golemati, S.,
Robust Carotid Artery Recognition in Longitudinal B-Mode Ultrasound Images,
IP(23), No. 9, September 2014, pp. 3762-3772.
IEEE DOI 1410
blood vessels BibRef

Kawai, F.[Fumi], Kondo, S.[Satoshi], Hayata, K.[Keisuke], Ohmiya, J.[Jun], Ishikawa, K.[Kiyoko], Yamamoto, M.[Masahiro],
Automatic Detection of the Carotid Artery Location from Volumetric Ultrasound Images Using Anatomical Position-Dependent LBP Features,
IEICE(E98-D), No. 7, July 2015, pp. 1353-1364.
WWW Link. 1508
BibRef

Tang, S.[Szeling], Chan, C.S.[Chee Seng],
Orthogonal planar search (OPS) for coronary artery centerline extraction,
SIViP(10), No. 1, February 2016, pp. 335-342.
WWW Link. 1601
BibRef

Lesage, D.[David], Angelini, E.D.[Elsa D.], Funka-Lea, G.[Gareth], Bloch, I.[Isabelle],
Adaptive particle filtering for coronary artery segmentation from 3D CT angiograms,
CVIU(151), No. 1, 2016, pp. 29-46.
Elsevier DOI 1610
3D CTA BibRef

Khedmati, A., Nikravanshalmani, A., Salajegheh, A.,
Semi-automatic detection of coronary artery stenosis in 3D CTA,
IET-IPR(10), No. 10, 2016, pp. 724-732.
DOI Link 1610
cardiology BibRef

Cui, H.F.[Heng-Fei], Xia, Y.[Yong], Zhang, Y.N.[Yan-Ning], Zhong, L.[Liang],
Validation of right coronary artery lumen area from cardiac computed tomography against intravascular ultrasound,
MVA(29), No. 8, November 2018, pp. 1287-1298.
WWW Link. 1811
BibRef

Qin, B.J.[Bin-Jie], Jin, M.X.[Ming-Xin], Hao, D.D.[Dong-Dong], Lv, Y.S.[Yi-Song], Liu, Q.[Qiegen], Zhu, Y.Q.[Yue-Qi], Ding, S.[Song], Zhao, J.[Jun], Fei, B.W.[Bao-Wei],
Accurate vessel extraction via tensor completion of background layer in X-ray coronary angiograms,
PR(87), 2019, pp. 38-54.
Elsevier DOI 1812
X-ray coronary angiography, Tensor completion, Robust principal component analysis, Vessel segmentation, Vessel recovery BibRef

Olender, M.L., Athanasiou, L.S., de la Torre Hernández, J.M., Ben-Assa, E., Nezami, F.R., Edelman, E.R.,
A Mechanical Approach for Smooth Surface Fitting to Delineate Vessel Walls in Optical Coherence Tomography Images,
MedImg(38), No. 6, June 2019, pp. 1384-1397.
IEEE DOI 1906
Surface fitting, Fitting, Springs, Interpolation, Medical diagnostic imaging, Border detection, coronary arteries, vessels BibRef

Zreik, M., van Hamersvelt, R.W., Wolterink, J.M., Leiner, T., Viergever, M.A., Išgum, I.,
A Recurrent CNN for Automatic Detection and Classification of Coronary Artery Plaque and Stenosis in Coronary CT Angiography,
MedImg(38), No. 7, July 2019, pp. 1588-1598.
IEEE DOI 1907
Arteries, Feature extraction, Computed tomography, Task analysis, Visualization, Biomedical imaging, Atherosclerosis, automatic classification BibRef

Petersen, J., Arias-Lorza, A.M., Selvan, R., Bos, D., van der Lugt, A., Pedersen, J.H., Nielsen, M., de Bruijne, M.,
Increasing Accuracy of Optimal Surfaces Using Min-Marginal Energies,
MedImg(38), No. 7, July 2019, pp. 1559-1568.
IEEE DOI 1907
Biomedical imaging, Rough surfaces, Surface roughness, Labeling, Uncertainty, Image segmentation, Memory management, Segmentation, carotid arteries BibRef

Jeon, B.[Byunghwan], Jang, Y.G.[Yeong-Gul], Shim, H.[Hackjoon], Chang, H.J.[Hyuk-Jae],
Identification of coronary arteries in CT images by Bayesian analysis of geometric relations among anatomical landmarks,
PR(96), 2019, pp. 106958.
Elsevier DOI 1909
Computed tomography angiography, Bayesian, Localization, Coronary artery, Multiple target, Curve analysis, Curvature and torsion BibRef

Edwards, M.[Michael], Xie, X.H.[Xiang-Hua], Palmer, R.I.[Robert I.], Tam, G.K.L.[Gary K.L.], Alcock, R.[Rob], Roobottom, C.[Carl],
Graph convolutional neural network for multi-scale feature learning,
CVIU(194), 2020, pp. 102881.
Elsevier DOI 2005
Deep learning, Graph convolutional neural network, Medical image segmentation, Marginal space learning, Computerized tomography BibRef

Deng, J.J.[Jing-Jing], Xie, X.H.[Xiang-Hua], Alcock, R.[Rob], Roobottom, C.[Carl],
3D interactive coronary artery segmentation using random forests and Markov random field optimization,
ICIP14(942-946)
IEEE DOI 1502
Arteries BibRef

Gao, Z., Chung, J., Abdelrazek, M., Leung, S., Hau, W.K., Xian, Z., Zhang, H., Li, S.,
Privileged Modality Distillation for Vessel Border Detection in Intracoronary Imaging,
MedImg(39), No. 5, May 2020, pp. 1524-1534.
IEEE DOI 2005
Vessel border detection, privileged information, knowledge distillation, intravascular ultrasound, optical coherence tomography BibRef

Zreik, M., van Hamersvelt, R.W., Khalili, N., Wolterink, J.M., Voskuil, M., Viergever, M.A., Leiner, T., Išgum, I.,
Deep Learning Analysis of Coronary Arteries in Cardiac CT Angiography for Detection of Patients Requiring Invasive Coronary Angiography,
MedImg(39), No. 5, May 2020, pp. 1545-1557.
IEEE DOI 2005
Functionally significant coronary artery stenosis, convolutional autoencoder, convolutional neural network, deep learning BibRef

Fang, H., Zhu, J., Ai, D., Huang, Y., Jiang, Y., Song, H., Wang, Y., Yang, J.,
Greedy Soft Matching for Vascular Tracking of Coronary Angiographic Image Sequences,
CirSysVideo(30), No. 5, May 2020, pp. 1466-1480.
IEEE DOI 2005
Target tracking, Topology, Bifurcation, Image sequences, GSM, Optimization, Integrated circuit modeling, Branch matching, vascular tracking BibRef

Nasarian, E.[Elham], Abdar, M.[Moloud], Fahami, M.A.[Mohammad Amin], Alizadehsani, R.[Roohallah], Hussain, S.[Sadiq], Basiri, M.E.[Mohammad Ehsan], Zomorodi-Moghadam, M.[Mariam], Zhou, X.[Xujuan], Plawiak, P.[Pawel], Acharya, U.R.[U. Rajendra], Tan, R.S.[Ru-San], Sarrafzadegan, N.[Nizal],
Association between work-related features and coronary artery disease: A heterogeneous hybrid feature selection integrated with balancing approach,
PRL(133), 2020, pp. 33-40.
Elsevier DOI 2005
Machine learning, Data mining, Heart disease, Coronary artery disease, Feature selection BibRef

Sukanya, A.[Arumugham], Rajeswari, R.[Rajendran], Murugan, K.S.[Kamatchigounder Subramaniam],
Region based coronary artery segmentation using modified Frangi's vesselness measure,
IJIST(30), No. 3, 2020, pp. 716-730.
DOI Link 2008
centerline extraction, coronary artery segmentation, coronary computed tomography angiography, vesselness measure BibRef

Zhou, R., Guo, F., Azarpazhooh, M.R., Spence, J.D., Ukwatta, E., Ding, M., Fenster, A.,
A Voxel-Based Fully Convolution Network and Continuous Max-Flow for Carotid Vessel-Wall-Volume Segmentation From 3D Ultrasound Images,
MedImg(39), No. 9, September 2020, pp. 2844-2855.
IEEE DOI 2009
Image segmentation, Feature extraction, Imaging, Atherosclerosis, continuous max-flow BibRef

Zhang, D., Yang, G., Zhao, S., Zhang, Y., Ghista, D., Zhang, H., Li, S.,
Direct Quantification of Coronary Artery Stenosis Through Hierarchical Attentive Multi-View Learning,
MedImg(39), No. 12, December 2020, pp. 4322-4334.
IEEE DOI 2012
Arteries, Lesions, Task analysis, Image reconstruction, Correlation, Feature extraction, Estimation, direct quantification, coronary artery stenosis BibRef

Ning, Y.[Yang], Zhang, Y.F.[Yun-Feng], Li, X.M.[Xue-Mei], Zhang, C.M.[Cai-Ming],
Towards accurate coronary artery calcium segmentation with multi-scale attention mechanism,
IET-IPR(15), No. 6, 2021, pp. 1359-1370.
DOI Link 2106
BibRef

Qi, Y.L.[Yao-Lei], Xu, H.[Han], He, Y.T.[Yu-Ting], Li, G.Y.[Guan-Yu], Li, Z.H.[Ze-Hang], Kong, Y.Y.[You-Yong], Coatrieux, J.L.[Jean-Louis], Shu, H.Z.[Hua-Zhong], Yang, G.[Guanyu], Tu, S.X.[Sheng-Xian],
Examinee-Examiner Network: Weakly Supervised Accurate Coronary Lumen Segmentation Using Centerline Constraint,
IP(30), 2021, pp. 9429-9441.
IEEE DOI 2112
Image segmentation, Task analysis, Arteries, Supervised learning, Lesions, Feature extraction, Training, CT angiography image BibRef

Li, C.[Chao], Jia, H.B.[Hai-Bo], Tian, J.[Jinwei], He, C.[Chong], Lu, F.[Fang], Li, K.W.[Kai-Wen], Gong, Y.[Yubin], Hu, S.[Sining], Yu, B.[Bo], Wang, Z.[Zhao],
Comprehensive Assessment of Coronary Calcification in Intravascular OCT Using a Spatial-Temporal Encoder-Decoder Network,
MedImg(41), No. 4, April 2022, pp. 857-868.
IEEE DOI 2204
Image segmentation, Spatial resolution, Imaging, Medical services, Lesions, Planning, Calcification, convolutional neural networks, optical coherence tomography BibRef

Rjiba, S.[Saifeddine], Urruty, T.[Thierry], Bourdon, P.[Pascal], Fernandez-Maloigne, C.[Christine], Delepaule, R.[Roger], Christiaens, L.P.[Luc-Philippe], Guillevin, R.[Remy],
CenterlineNet: Automatic Coronary Artery Centerline Extraction for Computed Tomographic Angiographic Images Using Convolutional Neural Network Architectures,
IPTA20(1-6)
IEEE DOI 2206
Heart, Pipelines, Feature extraction, Data mining, Convolutional neural networks, Arteries BibRef

Wu, W.[Wei], Zhang, J.Y.[Jing-Yang], Peng, W.J.[Wen-Jia], Xie, H.Z.[Hong-Zhi], Zhang, S.Y.[Shu-Yang], Gu, L.[Lixu],
CAR-Net: A Deep Learning-Based Deformation Model for 3D/2D Coronary Artery Registration,
MedImg(41), No. 10, October 2022, pp. 2715-2727.
IEEE DOI 2210
Arteries, Strain, Image segmentation, Bifurcation, Solid modeling, Detectors, 3D/2D coronary artery registration, deep learning, angular deflections prediction BibRef

Qin, B.J.[Bin-Jie], Mao, H.H.[Hao-Hao], Liu, Y.M.[Yi-Ming], Zhao, J.[Jun], Lv, Y.S.[Yi-Song], Zhu, Y.Q.[Yue-Qi], Ding, S.[Song], Chen, X.[Xu],
Robust PCA Unrolling Network for Super-Resolution Vessel Extraction in X-Ray Coronary Angiography,
MedImg(41), No. 11, November 2022, pp. 3087-3098.
IEEE DOI 2211
Feature extraction, Spatiotemporal phenomena, Noise measurement, Computational modeling, Image segmentation, Data mining, super-resolution BibRef

Zhang, H.W.[Hong-Wei], Gao, Z.[Zhifan], Zhang, D.[Dong], Hau, W.K.[William Kongto], Zhang, H.[Heye],
Progressive Perception Learning for Main Coronary Segmentation in X-Ray Angiography,
MedImg(42), No. 3, March 2023, pp. 864-879.
IEEE DOI 2303
Semantics, Interference, Image segmentation, Feature extraction, X-ray imaging, Lesions, Transformers, Progressive perception, X-ray angiography BibRef

Arora, P.[Priyanka], Singh, P.[Parminder], Girdhar, A.[Akshay], Vijayvergiya, R.[Rajesh],
Performance analysis of various denoising filters on intravascular ultrasound coronary artery images,
IJIST(33), No. 3, 2023, pp. 965-984.
DOI Link 2305
coronary artery stenosis, image denoising, Intravascular Ultrasound, speckle noise BibRef

Yang, S.[Shimeng], Li, T.[Teng], Lv, Y.[Yinping], Xia, Y.[Yi], Li, S.[Shuo],
Carotid Lumen Diameter and Intima-Media Thickness Measurement via Boundary-Guided Pseudo-Labeling,
SPLetters(30), 2023, pp. 1027-1031.
IEEE DOI 2309
BibRef

Jiang, M.J.[Ming-Jie], Chiu, B.[Bernard],
A Dual-Stream Centerline-Guided Network for Segmentation of the Common and Internal Carotid Arteries From 3D Ultrasound Images,
MedImg(42), No. 9, September 2023, pp. 2690-2705.
IEEE DOI 2310
BibRef

Singh, B.K.[Bikesh Kumar], Dutta, S.[Sonali], Chand, P.[Poonam], Kumar, K.[Khilesh], Banchhor, S.K.[Sumit Kumar],
An improved multi-criteria-based feature selection approach for detection of coronary artery disease in machine learning paradigm,
IJCVR(13), No. 5, 2023, pp. 533-555.
DOI Link 2310
BibRef

Zhao, C.[Chen], Xu, Z.H.[Zhi-Hui], Jiang, J.[Jingfeng], Esposito, M.[Michele], Pienta, D.[Drew], Hung, G.U.[Guang-Uei], Zhou, W.H.[Wei-Hua],
AGMN: Association graph-based graph matching network for coronary artery semantic labeling on invasive coronary angiograms,
PR(143), 2023, pp. 109789.
Elsevier DOI 2310
Coronary artery disease, Coronary arterial anatomy, Semantic labeling, Graph matching network BibRef

Fu, Z.[Zeyu], Fu, Z.[Zhuang], Lu, C.[Chenzhuo], Yan, J.[Jun], Fei, J.[Jian], Han, H.[Hui],
Robust implementation of foreground extraction and vessel segmentation for X-ray coronary angiography image sequence,
PR(145), 2024, pp. 109926.
Elsevier DOI 2311
X-ray coronary angiography, Tensor RPCA, TV regularization, Two-stage region growing, Foreground extraction, Vessel segmentation BibRef

Kowsalyadevi, J., Geetha, P.,
Predicting coronary artery disease using learning rate based snow leopard optimization with soft swish scaling based bidirectional long short-term memory,
IJIST(34), No. 1, 2024, pp. e22963.
DOI Link 2401
classification, clustering, coronary artery disease, detection, early diagnosis, feature selection, learning rate, segmentation BibRef

Zhang, X.[Xiao], Sun, K.[Kaicong], Wu, D.[Dijia], Xiong, X.S.[Xiao-Song], Liu, J.[Jiameng], Yao, L.L.[Lin-Lin], Li, S.[Shufang], Wang, Y.[Yining], Feng, J.[Jun], Shen, D.G.[Ding-Gang],
An Anatomy- and Topology-Preserving Framework for Coronary Artery Segmentation,
MedImg(43), No. 2, February 2024, pp. 723-733.
IEEE DOI 2402
Arteries, Topology, Image segmentation, Biomedical imaging, Heart, Feature extraction, Encoding, Coronary artery segmentation, coarse-to-fine segmentation BibRef


Evripides, G.[George], Christodoulides, P.[Paul], Loizou, C.P.[Christos P.],
Texture Analysis Contribution to Evaluate the Common Carotid Artery's Cardiovascular Disease (cvd) Risk Using Structural Equation Modeling,
CAIP23(I:227-236).
Springer DOI 2312
BibRef

Liapi, G.D.[Georgia D.], Markides, C.[Christos], Loizou, C.P.[Christos P.], Griffin, M.[Maura], Nicolaides, A.[Andrew], Kyriacou, E.[Efthyvoulos],
Stroke Risk Stratification Using Transfer Learning on Carotid Ultrasound Images,
CAIP23(II:130-139).
Springer DOI 2312
BibRef

Viti, M.[Mario], Talbot, H.[Hugues], Abdallah, B.[Bassam], Perot, E.[Etienne], Gogin, N.[Nicolas],
Coronary Artery Centerline Tracking with the Morphological Skeleton Loss,
ICIP22(2741-2745)
IEEE DOI 2211
Computed tomography, Angiography, Imaging, Skeleton, Reliability, Arteries, CT angiography, segmentation, blood vessels, deep learning BibRef

Arvidsson, I.[Ida], Overgaard, N.C.[Niels Christian], Ĺström, K.[Kalle], Heyden, A.[Anders], Figueroa, M.O.[Miguel Ochoa], Rose, J.F.[Jeronimo Frias], Davidsson, A.[Anette],
Prediction of Obstructive Coronary Artery Disease from Myocardial Perfusion Scintigraphy using Deep Neural Networks,
ICPR21(4442-4449)
IEEE DOI 2105
Medical services, Myocardium, Prediction algorithms, Classification algorithms, Risk management, Reliability, Task analysis BibRef

Shen, H., Zhang, W., Wang, H., Ding, G., Xie, J.,
NDDR-LCS: A Multi-Task Learning Method for Classification of Carotid Plaques,
ICIP20(2461-2465)
IEEE DOI 2011
Task analysis, Ultrasonic imaging, Feature extraction, Atherosclerosis, Dimensionality reduction, Image analysis, Ultrasound Reports BibRef

Li, D.H.[Dong-Hang], Barbu, A.[Adrian],
Training a Steerable CNN for Guidewire Detection,
CVPR20(13952-13960)
IEEE DOI 2008
used in coronary angioplasty. Training, Feature extraction, X-ray imaging, Convolution, Convolutional neural networks, Wires BibRef

Yang, H., Zhen, X., Chi, Y., Zhang, L., Hua, X.,
CPR-GCN: Conditional Partial-Residual Graph Convolutional Network in Automated Anatomical Labeling of Coronary Arteries,
CVPR20(3802-3810)
IEEE DOI 2008
Arteries, Feature extraction, Labeling, Solid modeling, Machine learning, Kernel BibRef

Blaiech, A.G.[Ahmed Ghazi], Mansour, A.[Asma], Kerkeni, A.[Asma], Bedoui, M.H.[Mohamed Hédi], Abdallah, A.B.[Asma Ben],
Impact of Enhancement for Coronary Artery Segmentation Based on Deep Learning Neural Network,
IbPRIA19(II:260-272).
Springer DOI 1910
BibRef

Çimen, S.[Serkan], Unberath, M.[Mathias], Frangi, A.[Alejandro], Maier, A.[Andreas],
CoronARe: A Coronary Artery Reconstruction Challenge,
RAMBO17(96-104).
Springer DOI 1711
BibRef

Poulain, E.[Emmanuelle], Malandain, G.[Grégoire], Vaillant, R.[Régis],
3D Coronary Vessel Tree Tracking in X-Ray Projections,
FIMH19(388-396).
Springer DOI 1906
BibRef
Earlier:
3D Coronary Vessel Tracking in X-Ray Projections,
FIMH17(204-215).
Springer DOI 1706
BibRef

Wang, C.L.[Chun-Liang], Wang, Q.[Qian], Smedby, Ö.[Örjan],
Automatic Heart and Vessel Segmentation Using Random Forests and a Local Phase Guided Level Set Method,
RAMBO16(159-164).
Springer DOI 1703
BibRef

Lösel, P.[Philipp], Heuveline, V.[Vincent],
A GPU Based Diffusion Method for Whole-Heart and Great Vessel Segmentation,
RAMBO16(121-128).
Springer DOI 1703
BibRef

Sofian, H., Muhammad, S., Ming, J.T.C.[Joel Than Chia], Noor, N.M.,
Lumen coronary artery border detection using texture and Chi-square classification,
ICVNZ15(1-6)
IEEE DOI 1701
biomedical ultrasonics BibRef

Smith, J.P.[Jordan P.], Shehata, M.[Mohamed], McGuire, P.F.[Peter F.], Smith, A.J.[Andrew J.],
Features of Internal Jugular Vein Contours for Classification,
ISVC16(II: 421-430).
Springer DOI 1701
BibRef

Harish Kumar, J.R., Seelamantula, C.S., Andrade, J., Rajagopal, K.V.,
Automatic Segmentation of Lumen Intima Layer in Transverse Mode Ultrasound Images,
ICIP18(3493-3497)
IEEE DOI 1809
Image segmentation, Carotid arteries, Ultrasonic imaging, Blood, Motion segmentation, Biomedical imaging, Media, active disc BibRef

Harish Kumar, J.R., Seelamantula, C.S., Narayan, N.S., Marziliano, P.,
Automatic segmentation of common carotid artery in transverse mode ultrasound images,
ICIP16(389-393)
IEEE DOI 1610
Atherosclerosis BibRef

Debbich, A., Kerkni, A., Abdallah, A.B., Salem, R., Clarysse, P., Bedoui, M.H.,
Hemodynamic Modeling in a Stenosed Internal Carotid Artery,
CGiV16(358-363)
IEEE DOI 1608
Navier-Stokes equations BibRef

Kerkeni, A., Abdallah, A.B., Manzanera, A., Bedoui, M.H.,
Automatic Bifurcation Detection in Coronary X-Ray Angiographies,
CGiV16(333-338)
IEEE DOI 1608
Hessian matrices BibRef

Uus, A., Liatsis, P., Jawaid, M.M., Rajani, R., Benderskaya, E.,
Assessment of stenosis introduced flow resistance in CCTA-reconstructed coronary arteries,
WSSIP15(313-320)
IEEE DOI 1603
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Hierarchical segmentation and tracking of coronary arteries in 2D X-ray Angiography sequences,
ICIP15(1707-1711)
IEEE DOI 1512
Coronary Arteries BibRef

Fazlali, H.R., Karimi, N., Soroushmehr, S.M.R., Sinha, S., Samavi, S., Nallamothu, B., Najarian, K.,
Vessel region detection in coronary X-ray angiograms,
ICIP15(1493-1497)
IEEE DOI 1512
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Jin, D.[Dakai], Iyer, K.S.[Krishna S.], Hoffman, E.A.[Eric A.], Saha, P.K.[Punam K.],
Automated Assessment of Pulmonary Arterial Morphology in Multi-row Detector CT Imaging Using Correspondence with Anatomic Airway Branches,
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Chen, Y.[Yang], Cao, Q.[Qing], Zhuang, Z.K.[Zhi-Kun], Yang, Z.[Zhou], Luo, L.M.[Li-Min], Toumoulin, C.[Christine],
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ICIAR13(502-509).
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ICIAR13(510-520).
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Zheng, Y.F.[Ye-Feng], Shen, J.H.[Jian-Hua], Tek, H.[Huseyin], Funka-Lea, G.[Gareth],
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WBIR12(131-140).
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Zhong, H.[Hua], Zheng, Y.F.[Ye-Feng], Funka-Lea, G.[Gareth], Vega-Higuera, F.[Fernando],
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MCV12(24-30).
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Serradell, E.[Eduard], Romero, A.[Adriana], Leta, R.[Ruben], Gatta, C.[Carlo], Moreno-Noguer, F.[Francesc],
Simultaneous correspondence and non-rigid 3D reconstruction of the coronary tree from single X-ray images,
ICCV11(850-857).
IEEE DOI 1201
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Pal, D.[Debabrata], Chakraborty, C.[Chandan], Mandana, K.M.,
Data mining approach for coronary artery disease screening,
ICIIP11(1-6).
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Lu, X.G.[Xiao-Guang], Chen, T.[Terrence], Comaniciu, D.[Dorin],
Robust discriminative wire structure modeling with application to stent enhancement in fluoroscopy,
CVPR11(1121-1127).
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Silva, S.[Samuel], Bettencourt, N.[Nuno], Leite, D.[Daniel], Rocha, J.[Joăo], Carvalho, M.[Mónica], Madeira, J.[Joaquim], Santos, B.S.[Beatriz Sousa],
Myocardial Perfusion Analysis from Adenosine-Induced Stress MDCT,
IbPRIA11(717-725).
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Gatta, C.[Carlo], Balocco, S.[Simone], Martin-Yuste, V.[Victoria], Leta, R.[Ruben], Radeva, P.[Petia],
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Qian, Z.[Zhen], Joshi, P.[Parag], Rinehart, S.[Sarah], Voros, S.[Szilard],
An Automated Segmentation and Classification Framework for CT-Based Myocardial Perfusion Imaging for Detecting Myocardial Perfusion Defect,
FIMH11(206-214).
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Dutta, S.[Sara], Bishop, M.J.[Martin J.], Pathmanathan, P.[Pras], Lee, P.[Peter], Kohl, P.[Peter], Quinn, T.A.[T. Alexander], Rodriguez, B.[Blanca],
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FIMH11(20-27).
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Bastida-Jumilla, M.C., Morales-Sanchez, J., Verdu-Monedero, R., Larrey-Ruiz, J., Sancho-Gomez, J.L.,
Detection of the intima and media walls of the carotid artery with geodesic active contours,
ICIP10(2213-2216).
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Azar, J.C.[Jimmy C.], Muhammed, H.H.[Hamed Hamid],
Automated Tracking of the Carotid Artery in Ultrasound Image Sequences Using a Self Organizing Neural Network,
ICPR10(2544-2547).
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Lu, L.[Le], Bi, J.[Jinbo], Yu, S.P.[Shi-Peng], Peng, Z.G.[Zhi-Gang], Krishnan, A.[Arun], Zhou, X.S.[Xiang Sean],
Hierarchical learning for tubular structure parsing in medical imaging: A study on coronary arteries using 3D CT Angiography,
ICCV09(2021-2028).
IEEE DOI 0909
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Kukar, M.[Matjaž], Šajn, L.[Luka],
Supporting Diagnostics of Coronary Artery Disease with Multi-resolution Image Parameterization and Data Mining,
MIRAGE09(356-367).
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Bismuth, V.[Vincent], Vaillant, R.[Regis],
A device enhancing and denoising algorithm for X-ray cardiac fluoroscopy,
ICPR08(1-4).
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Elastic registration for stent enhancement in X-ray image sequences,
ICIP08(2400-2403).
IEEE DOI 0810
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Nwogu, I.[Ifeoma], Lorigo, L.M.[Liana M.],
Fast Temporal Tracking and 3D Reconstruction of a Single Coronary Vessel,
ICIP07(V: 537-540).
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Fallavollita, P.[Pascal], Cheriet, F.[Farida],
Robust Coronary Artery Tracking from Fluoroscopic Image Sequences,
ICIAR07(889-898).
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Köse, C.[Cemal],
Fully Automatic Segmentation of Coronary Vessel Structures in Poor Quality X-Ray Angiogram Images,
SSPR06(74-82).
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Shape Particle Guided Tissue Classification,
MMBIA06(64).
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Zhang, Q.L.[Qi-Long], Pless, R.[Robert],
Segmenting Cardiopulmonary Images Using Manifold Learning with Level Sets,
CVBIA05(479-488).
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Hadar, E., Hahiashvili, Z., Aravot, D.,
The H2 Length Estimation Method: An Algorithm for Digitized Curves for Asymmetric 3D Grid Applied on Coronary Bypass Surgery,
ICIP05(I: 1121-1124).
IEEE DOI 0512
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Bouattour, S., Arndt, R., Paulus, D.,
4D Reconstruction of Coronary Arteries from Monoplane Angiograms,
CAIP05(724).
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Isgum, I., van Ginneken, B., Prokop, M.,
A pattern recognition approach to automated coronary calcium scoring,
ICPR04(III: 746-749).
IEEE DOI 0409
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Bellemare, C., Meunier, J.,
Structural method for tracking coronary arteries in coronary cineangiograms,
CRV04(378-384).
IEEE DOI 0408
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Cheng, D.C.[Da-Chuan], Schmidt-Trucksass, A., Cheng, K.S.[Kuo-Sheng], Sandrock, M., Pu, Q.[Qin], Burkhardt, H.,
Automatic detection of the intimal and the adventitial layers of the common carotid artery wall in ultrasound B-mode images using snakes,
CIAP99(452-457).
IEEE DOI 9909
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Ukai, Y., Niki, N., Satoh, H., Watanabe, S., Ohmatsu, H., Eguchi, K., Moriyama, N.,
An Algorithm for Coronary Calcification Diagnosis Based on Helical CT Images,
ICPR96(III: 543-547).
IEEE DOI 9608
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Zhang, X.M.[Xiang-Min], Collins, S.M., Sonka, M.,
Tree pruning strategy in automated detection of coronary trees in cineangiograms,
ICIP95(III: 656-659).
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Suetens, P., Smets, C., van de Werf, F., Oosterlinck, A.,
Recognition of the coronary blood vessels on angiograms using hierarchical model-based iconic search,
CVPR89(576-581).
IEEE DOI 0403
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Wang, R., Sklansky, J.,
Multiresolution method for reconstructing the cross sections of coronary arteries from biplane angiograms,
ICPR92(III:667-670).
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Harpaz, N., Shani, U., Dinar, U.,
Towards the automatic reconstruction of a 3-D animated model for the coronary tree from biplane angiograms,
ICPR88(II: 1012-1014).
IEEE DOI 8811
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Kitamura, K., Tobis, J.M., Sklansky, J.,
Biplane analysis of atheromatous coronary arteries,
ICPR88(II: 1277-1281).
IEEE DOI 8811
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Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Medical Applications -- Aorta, Aortic Analysis .


Last update:Mar 16, 2024 at 20:36:19