Automatic cardiac evaluations using a deep video object segmentation network

[1] Lang RM(2006)Recommendations for chamber quantification Eur J Echocardiogr 7 79-108

[2] Bierig M(2015)Semi-automated echocardiographic quantification of right ventricular size and function Int J Cardiovasc Imaging 31 1149-1157

[3] Devereux RB(2013)Combining multiple dynamic models and deep learning architectures for tracking the left ventricle endocardium in ultrasound data IEEE Trans Pattern Anal Mach Intell 35 2592-2607

[4] Medvedofsky D(2002)3-D active appearance models: segmentation of cardiac MR and ultrasound images IEEE Trans Med Imaging 21 1167-1178

[5] Addetia K(2002)Automatic segmentation of echocardiographic sequences by active appearance motion models IEEE Trans Med Imaging 21 1374-1383

[6] Hamilton J(2003)Applying improved fast marching method to endocardial boundary detection in echocardiographic images Pattern Recognit Lett 24 2777-2784

[7] Carneiro G(2003)Combinative multi-scale level set framework for echocardiographic image segmentation Med Image Anal 7 529-537

[8] Nascimento JC(2019)MFP-Unet: A novel deep learning based approach for left ventricle segmentation in echocardiography Phys Med 67 58-69

[9] Mitchell SC(2014)Whole myocardium tracking in 2D-echocardiography in multiple orientations using a motion constrained level-set Med Image Anal 18 500-514

[10] Bosch JG(2003)A GA based approach for boundary detection of left ventricle with echocardiographic image sequences Image Vision Comput 21 967-976

[1] Lang RM(2006)Recommendations for chamber quantification Eur J Echocardiogr 7 79-108

[2] Bierig M(2015)Semi-automated echocardiographic quantification of right ventricular size and function Int J Cardiovasc Imaging 31 1149-1157

[3] Devereux RB(2013)Combining multiple dynamic models and deep learning architectures for tracking the left ventricle endocardium in ultrasound data IEEE Trans Pattern Anal Mach Intell 35 2592-2607

[4] Medvedofsky D(2002)3-D active appearance models: segmentation of cardiac MR and ultrasound images IEEE Trans Med Imaging 21 1167-1178

[5] Addetia K(2002)Automatic segmentation of echocardiographic sequences by active appearance motion models IEEE Trans Med Imaging 21 1374-1383

[6] Hamilton J(2003)Applying improved fast marching method to endocardial boundary detection in echocardiographic images Pattern Recognit Lett 24 2777-2784

[7] Carneiro G(2003)Combinative multi-scale level set framework for echocardiographic image segmentation Med Image Anal 7 529-537

[8] Nascimento JC(2019)MFP-Unet: A novel deep learning based approach for left ventricle segmentation in echocardiography Phys Med 67 58-69

[9] Mitchell SC(2014)Whole myocardium tracking in 2D-echocardiography in multiple orientations using a motion constrained level-set Med Image Anal 18 500-514

[10] Bosch JG(2003)A GA based approach for boundary detection of left ventricle with echocardiographic image sequences Image Vision Comput 21 967-976