메뉴 건너뛰기




Volumn 43, Issue , 2016, Pages 89-92

A novel left ventricular volumes prediction method based on deep learning network in cardiac MRI

Author keywords

[No Author keywords available]

Indexed keywords

CARDIOLOGY; DIAGNOSIS; HEART; LARGE DATASET;

EID: 85016133285     PISSN: 23258861     EISSN: 2325887X     Source Type: Conference Proceeding    
DOI: 10.22489/cinc.2016.028-224     Document Type: Conference Paper
Times cited : (35)

References (13)
  • 1
    • 84969930014 scopus 로고    scopus 로고
    • Non-invasive cardiac imaging: Past, present and future
    • Selvanayagam JB. Non-Invasive Cardiac Imaging: Past, Present and Future. Heart, lung & circulation. 2016;25 (8): 755-6.
    • (2016) Heart, Lung & Circulation. , vol.25 , Issue.8 , pp. 755-756
    • Selvanayagam, J.B.1
  • 3
    • 84958955334 scopus 로고    scopus 로고
    • A combined deeplearning and deformable-model approach to fully automatic segmentation of the left ventricle in cardiac MRI
    • Avendi MR, Kheradvar A, Jafarkhani H. A combined deeplearning and deformable-model approach to fully automatic segmentation of the left ventricle in cardiac MRI. Med Image Anal. 2016;30: 108-19.
    • (2016) Med Image Anal. , vol.30 , pp. 108-119
    • Avendi, M.R.1    Kheradvar, A.2    Jafarkhani, H.3
  • 5
    • 85016124927 scopus 로고    scopus 로고
    • A combined multi-scale deep learning and random forests approach for direct left ventricular volumes estimation in 3D echocardiography
    • Dong SY, Luo GN, Sun GX, Wang KQ, Zhang HG. A combined multi-scale deep learning and random forests approach for direct left ventricular volumes estimation in 3D echocardiography. Computing in Cardiology 2016;43.
    • (2016) Computing in Cardiology , vol.43
    • Dong, S.Y.1    Luo, G.N.2    Sun, G.X.3    Wang, K.Q.4    Zhang, H.G.5
  • 6
    • 84938394939 scopus 로고    scopus 로고
    • Big heart data: Advancing health informatics through data sharing in cardiovascular imaging
    • Suinesiaputra A, Medrano-Gracia P, Cowan BR, Young AA. Big Heart Data: Advancing Health Informatics Through Data Sharing in Cardiovascular Imaging. Ieee J Biomed Health. 2015;19 (4): 1283-90.
    • (2015) Ieee J Biomed Health. , vol.19 , Issue.4 , pp. 1283-1290
    • Suinesiaputra, A.1    Medrano-Gracia, P.2    Cowan, B.R.3    Young, A.A.4
  • 7
    • 79851510761 scopus 로고    scopus 로고
    • A review of segmentation methods in short axis cardiac MR images
    • Petitjean C, Dacher JN. A review of segmentation methods in short axis cardiac MR images. Medical Image Analysis. 2011;15 (2): 169-84.
    • (2011) Medical Image Analysis , vol.15 , Issue.2 , pp. 169-184
    • Petitjean, C.1    Dacher, J.N.2
  • 8
    • 84955240327 scopus 로고    scopus 로고
    • A review of heart chamber segmentation for structural and functional analysis using cardiac magnetic resonance imaging
    • Peng P, Lekadir K, Gooya A, Shao L, Petersen SE, Frangi AF. A review of heart chamber segmentation for structural and functional analysis using cardiac magnetic resonance imaging. Magma. 2016;29 (2): 155-95.
    • (2016) Magma , vol.29 , Issue.2 , pp. 155-195
    • Peng, P.1    Lekadir, K.2    Gooya, A.3    Shao, L.4    Petersen, S.E.5    Frangi, A.F.6
  • 9
    • 84969962996 scopus 로고    scopus 로고
    • Deep convolutional neural networks for computer-aided detection: CNN architectures, dataset characteristics and transfer learning
    • Shin HC, Roth HR, Gao M, Lu L, Xu Z, Nogues I, et al. Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning. IEEE Trans Med Imaging. 2016;35 (5): 1285-98.
    • (2016) IEEE Trans Med Imaging. , vol.35 , Issue.5 , pp. 1285-1298
    • Shin, H.C.1    Roth, H.R.2    Gao, M.3    Lu, L.4    Xu, Z.5    Nogues, I.6
  • 12
    • 84894041326 scopus 로고    scopus 로고
    • Regional assessment of cardiac left ventricular myocardial function via MRI statistical features
    • Afshin M, Ben Ayed I, Punithakumar K, Law M, Islam A, Goela A, et al. Regional assessment of cardiac left ventricular myocardial function via MRI statistical features. IEEE Trans Med Imaging. 2014;33 (2): 481-94.
    • (2014) IEEE Trans Med Imaging. , vol.33 , Issue.2 , pp. 481-494
    • Afshin, M.1    Ben Ayed, I.2    Punithakumar, K.3    Law, M.4    Islam, A.5    Goela, A.6
  • 13
    • 84958981335 scopus 로고    scopus 로고
    • Multiscale deep networks and regression forests for direct biventricular volume estimation
    • Zhen X, Wang Z, Islam A, Bhaduri M, Chan I, Li S. Multiscale deep networks and regression forests for direct biventricular volume estimation. Med Image Anal. 2016;30: 120-9.
    • (2016) Med Image Anal. , vol.30 , pp. 120-129
    • Zhen, X.1    Wang, Z.2    Islam, A.3    Bhaduri, M.4    Chan, I.5    Li, S.6


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.