{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T13:55:02Z","timestamp":1791813302759,"version":"4.3.4"},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2020,1,2]],"date-time":"2020-01-02T00:00:00Z","timestamp":1577923200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,2]],"date-time":"2020-01-02T00:00:00Z","timestamp":1577923200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Med Biol Eng Comput"],"published-print":{"date-parts":[[2020,3]]},"DOI":"10.1007\/s11517-019-02099-3","type":"journal-article","created":{"date-parts":[[2020,1,2]],"date-time":"2020-01-02T07:02:53Z","timestamp":1577948573000},"page":"471-482","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":35,"title":["Localization of common carotid artery transverse section in B-mode ultrasound images using faster RCNN: a deep learning approach"],"prefix":"10.1007","volume":"58","author":[{"given":"Pankaj K.","family":"Jain","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saurabh","family":"Gupta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arnav","family":"Bhavsar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aditya","family":"Nigam","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Neeraj","family":"Sharma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,1,2]]},"reference":[{"key":"2099_CR1","volume-title":"Promoting cardiovascular health in the developing world: a critical challenge to achieve global health","author":"BB Kelly","year":"2010","unstructured":"Kelly BB, Fuster V (2010) Promoting cardiovascular health in the developing world: a critical challenge to achieve global health. National Academies Press, Washington"},{"issue":"1","key":"2099_CR2","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1007\/s13244-010-0049-0","volume":"2","author":"K Nikolaou","year":"2011","unstructured":"Nikolaou K, Alkadhi H, Bamberg F, Leschka S, Wintersperger BJ (2011) MRI and CT in the diagnosis of coronary artery disease: indications and applications. Insights Into Imaging 2(1):9\u201324","journal-title":"Insights Into Imaging"},{"key":"2099_CR3","volume-title":"Multi-modality atherosclerosis imaging and diagnosis","author":"L Saba","year":"2015","unstructured":"Saba L, Sanches JM, Pedro LM, Suri JS (2015) Multi-modality atherosclerosis imaging and diagnosis. Springer, New York"},{"issue":"1","key":"2099_CR4","first-page":"112","volume":"3","author":"A Prakash","year":"2010","unstructured":"Prakash A, Powell AJ, Geva T (2010) Multimodality noninvasive imaging for assessment of congenital heart disease. Circ: Cardiovasc Imaging 3(1):112\u2013125","journal-title":"Circ: Cardiovasc Imaging"},{"issue":"1","key":"2099_CR5","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1080\/02656736.2018.1487591","volume":"35","author":"E Xu","year":"2019","unstructured":"Xu E, Long Y, Li K, Zeng Q, Tan L, Luo L, Zheng R (2019) Comparison of CT\/MRI-CEUS and US-CEUS fusion imaging techniques in the assessment of the thermal ablation of liver tumors. Int J Hyperth 35(1):159\u2013167","journal-title":"Int J Hyperth"},{"issue":"6","key":"2099_CR6","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1007\/s10916-017-0745-0","volume":"41","author":"L Saba","year":"2017","unstructured":"Saba L, Jain PK, Suri HS, Ikeda N, Araki T, Singh BK, Nicolaides A, Shafique S, Gupta A, Laird JR, Suri JS (2017) Plaque tissue morphology-based stroke risk stratification using carotid ultrasound: a polling-based PCA learning paradigm. J Med Syst 41(6):41\u201398","journal-title":"J Med Syst"},{"key":"2099_CR7","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1016\/j.cmpb.2016.02.004","volume":"128","author":"T Araki","year":"2016","unstructured":"Araki T, Ikeda N, Shukla D, Jain PK, Londhe ND, Shrivastava VK, Laird JR (2016) PCA-based polling strategy in machine learning framework for coronary artery disease risk assessment in intravascular ultrasound: a link between carotid and coronary grayscale plaque morphology. Comput Methods Prog Biomed 128:137\u2013158","journal-title":"Comput Methods Prog Biomed"},{"issue":"11","key":"2099_CR8","doi-asserted-by":"publisher","first-page":"1253","DOI":"10.1016\/S1885-5857(10)70250-4","volume":"63","author":"F N\u00fa\u00f1ez","year":"2010","unstructured":"N\u00fa\u00f1ez F, Mart\u00ednez-Costa C, S\u00e1nchez-Zahonero J, Morata J, Chorro FJ, Brines J (2010) Carotid artery stiffness as an early marker of vascular lesions in children and adolescents with cardiovascular risk factors. Revista Espa\u00f1ola de Cardiolog\u00eda (English Edition) 63(11):1253\u20131260","journal-title":"Revista Espa\u00f1ola de Cardiolog\u00eda (English Edition)"},{"key":"2099_CR9","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1016\/j.compbiomed.2016.11.011","volume":"80","author":"T Araki","year":"2017","unstructured":"Araki T, Jain PK, Suri HS, Londhe ND, Ikeda N, El-Baz A, Laird JR (2017) Stroke risk stratification and its validation using ultrasonic echolucent carotid wall plaque morphology: a machine learning paradigm. Comput Biol Med 80:77\u201396","journal-title":"Comput Biol Med"},{"key":"2099_CR10","doi-asserted-by":"crossref","unstructured":"\u0158\u00edha K and Bene\u0161 R (2010) Circle detection in pulsative medical video sequence IEEE 10th International Conference on Signal Processing (ICSP)","DOI":"10.1109\/ICOSP.2010.5655744"},{"issue":"1","key":"2099_CR11","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1016\/j.cmpb.2012.08.014","volume":"109","author":"R Benes","year":"2013","unstructured":"Benes R, Karasek J, Barget R, Riha K (2013) Automatically designed machine vision system for the localization of CCA transverse section in ultrasound images. Comput Methods Prog Biomed 109(1):92\u2013103","journal-title":"Comput Methods Prog Biomed"},{"issue":"10","key":"2099_CR12","doi-asserted-by":"publisher","first-page":"1887","DOI":"10.1016\/j.ultrasmedbio.2013.04.013","volume":"39","author":"K \u0158\u00edha","year":"2013","unstructured":"\u0158\u00edha K, Masek J, Benes R, Zavodana E (2013) Novel method for localization of common carotid artery transverse section in ultrasound images using modified Viola-Jones detector. Ultrasound Med Biol 39(10):1887\u20131902","journal-title":"Ultrasound Med Biol"},{"issue":"5","key":"2099_CR13","doi-asserted-by":"publisher","first-page":"15","DOI":"10.5815\/ijigsp.2011.05.03","volume":"3","author":"X Yang","year":"2011","unstructured":"Yang X, Mingyueg D, Liantang L, Ming Y, Qiu W, Yue S (2011) Common carotid artery lumen segmentation in B-mode ultrasound transverse view images. Int J Image, Graphics Signal Process 3(5):15\u201321","journal-title":"Int J Image, Graphics Signal Process"},{"key":"2099_CR14","unstructured":"Yoon YH, Khan S, Huh J, Ye JC (2017) Deep learning in RF sub-sampled B-mode ultrasound imaging. arXiv preprint arXiv:1712.06096"},{"key":"2099_CR15","unstructured":"Vedula S, Senouf O, Bronstein AM, Michailovich OV, Zibulevsky M (2017) Towards CT-quality ultrasound imaging using deep learning. arXiv preprint arXiv:1710.06304"},{"key":"2099_CR16","unstructured":"Perdios D, Besson A, Arditi M, Thiran JP (2014) A deep learning approach to ultrasound image recovery. IEEE International In Ultrasonics Symposium (IUS) 1-4"},{"issue":"5","key":"2099_CR17","doi-asserted-by":"publisher","first-page":"1299","DOI":"10.1109\/TMI.2016.2535302","volume":"35","author":"N Tajbakhsh","year":"2016","unstructured":"Tajbakhsh N, Shin JY, Gurudu SR, Hurst R, Kendall CB, Gotway MB, Liang J (2016) Convolutional neural networks for medical image analysis: full training or fine tuning? IEEE Trans Med Imaging 35(5):1299\u20131312","journal-title":"IEEE Trans Med Imaging"},{"issue":"5","key":"2099_CR18","doi-asserted-by":"publisher","first-page":"1678","DOI":"10.1002\/mp.12134","volume":"44","author":"J Ma","year":"2017","unstructured":"Ma J, Wu F, Zhu J, Kong D (2017) Cascade convolutional neural networks for automatic detection of thyroid nodules in ultrasound images. Med Phys 44(5):1678\u20131691","journal-title":"Med Phys"},{"issue":"8","key":"2099_CR19","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1007\/s10916-018-1001-y","volume":"42","author":"S Sudha","year":"2018","unstructured":"Sudha S, Jayanthi KB, Rajasekaran C, Madian N, Sunder T (2018) Convolutional neural network for segmentation and measurement of intima media thickness. J Med Syst 42(8):154","journal-title":"J Med Syst"},{"key":"2099_CR20","unstructured":"\u0158iha K and Igor P (2009) The sequential detection of artery sectional area using optical flow technique 8th WSEAS International Conference on Circuits, systems, electronics, control & signal processing, World Scientific and Engineering Academy and Society (WSEAS)"},{"key":"2099_CR21","unstructured":"\u0158iha K, Peng C, Dongmei F (2008) Detection of artery section area using artificial immune system algorithm. 7th WSEAS International Conference on Circuits, systems, electronics, control & signal processing, World Scientific and Engineering Academy and Society (WSEAS)"},{"key":"2099_CR22","doi-asserted-by":"crossref","unstructured":"Girshick R, Donahue J, Darrell T, Malik J (2015) Region-based convolutional networks for accurate object detectionand segmentation. TPAMI","DOI":"10.1109\/TPAMI.2015.2437384"},{"key":"2099_CR23","doi-asserted-by":"crossref","unstructured":"Girshick R (2015) Fast r-CNN. IEEE international conference on computer vision 1440-1448","DOI":"10.1109\/ICCV.2015.169"},{"key":"2099_CR24","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2014) Spatial pyramid pooling in deep convolutional networks for visual recognition. European Conference on Computer Vision, Springer, Cham, pp 346\u2013361","DOI":"10.1007\/978-3-319-10578-9_23"},{"key":"2099_CR25","unstructured":"Ren S, He K, Girshick R, Sun J (2015) Faster R-CNN: towards real-time object detection with region proposal networks. Adv Neural Inf Proces Syst:91\u201399"},{"key":"2099_CR26","doi-asserted-by":"crossref","unstructured":"Chan V, Perlas A Basics of ultrasound imaging. Atlas of ultrasound-guided procedures in interventional pain management. Springer, New York, pp 13\u201319","DOI":"10.1007\/978-1-4419-1681-5_2"},{"issue":"1","key":"2099_CR27","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1186\/2049-6958-8-18","volume":"8","author":"G Soldati","year":"2013","unstructured":"Soldati G, Smargiassi A, Inchingolo R, Sher S, Valente S, Corbo GM (2013) Ultrasound-guided pleural puncture in supine or recumbent lateral position - feasibility study. Multidiscipl Respiratory Med 8(1):8\u201318","journal-title":"Multidiscipl Respiratory Med"},{"key":"2099_CR28","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. IEEE conference on computer vision and pattern recognition 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"issue":"4","key":"2099_CR29","doi-asserted-by":"publisher","first-page":"814","DOI":"10.1109\/TPAMI.2015.2465908","volume":"38","author":"J Hosang","year":"2016","unstructured":"Hosang J, Benenson R, Doll\u00e1r P, Schiele B (2016) What makes for effective detection proposals? IEEE Trans Pattern Anal Mach Intell 38(4):814\u2013830","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"2099_CR30","unstructured":"Ultrasound image data set B-mode ultrasound images of the carotid artery transverse section are downloaded from www.splab.cz (accessed in April 2017)"}],"container-title":["Medical &amp; Biological Engineering &amp; Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-019-02099-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11517-019-02099-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-019-02099-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,9]],"date-time":"2022-10-09T18:27:09Z","timestamp":1665340029000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11517-019-02099-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,1,2]]},"references-count":30,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2020,3]]}},"alternative-id":["2099"],"URL":"https:\/\/doi.org\/10.1007\/s11517-019-02099-3","relation":{},"ISSN":["0140-0118","1741-0444"],"issn-type":[{"value":"0140-0118","type":"print"},{"value":"1741-0444","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,1,2]]},"assertion":[{"value":"9 October 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 December 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 January 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}