Recursive multiresolution convolutional neural networks for 3D aortic valve annulus planimetry

被引:0
作者
Pascal Theriault-Lauzier
Hind Alsosaimi
Negareh Mousavi
Jean Buithieu
Marco Spaziano
Giuseppe Martucci
James Brophy
Nicolo Piazza
机构
[1] University of Ottawa Heart Institute,Division of Cardiology
[2] McGill University Health Centre,Division of Cardiology
来源
International Journal of Computer Assisted Radiology and Surgery | 2020年 / 15卷
关键词
Heart; Neural network; Machine learning; Segmentation; X-ray imaging and computed tomography;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
页码:577 / 588
页数:11
相关论文
共 203 条
[1]  
Matiasz R(2018)2017 Focused update for management of patients with valvular heart disease: summary of new recommendations J Am Heart Assoc 7 e007596-20
[2]  
Rigolin VH(2019)Computed tomography imaging in the context of transcatheter aortic valve implantation (TAVI)/transcatheter aortic valve replacement (TAVR): an expert consensus document of the society of cardiovascular computed tomography J Cardiovasc Comput Tomogr 13 1-23
[3]  
Blanke P(2015)Three-dimensional echocardiography vs. computed tomography for transcatheter aortic valve replacement sizing Eur Heart J Cardiovasc Imag 17 15-661
[4]  
Weir-McCall J(2014)Erroneous measurement of the aortic annular diameter using 2-dimensional echocardiography resulting in inappropriate corevalve size selection JACC Cardiovasc Intervent 7 652-81
[5]  
Achenbach S(2008)Anatomy of the aortic valvar complex and its implications for transcatheter implantation of the aortic valve Circ Cardiovasc Interv 1 74-1888
[6]  
Delgado V(2014)Reproducibility of aortic annulus measurements by computed tomography Eur Radiol 24 1878-90
[7]  
Hausleiter J(2017)Imagenet classification with deep convolutional neural networks Commun ACM 60 84-551
[8]  
Jilaihawi H(1989)Backpropagation Applied to Handwritten Zip Code Recognition Neural Comput 1 541-2324
[9]  
Marwan M(1998)Gradient-based learning applied to document recognition Proc IEEE 86 2278-524
[10]  
Norgaard BL(1994)Computerized detection of clustered microcalcifications in digital mammograms using a shift-invariant artificial neural network Med Phys 21 517-1312