C
Christina Luong
Researcher at Vancouver General Hospital
Publications - 14
Citations - 223
Christina Luong is an academic researcher from Vancouver General Hospital. The author has contributed to research in topics: Deep learning & Echo (computing). The author has an hindex of 6, co-authored 14 publications receiving 153 citations.
Papers
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Journal ArticleDOI
Correction to “Automatic Quality Assessment of Echocardiograms Using Convolutional Neural Networks: Feasibility on the Apical Four-Chamber View”
Amir H. Abdi,Christina Luong,Teresa Tsang,Gregory Allan,Saman Nouranian,John Jue,Dale Hawley,Sarah Fleming,Ken Gin,Jody Swift,Robert Rohling,Purang Abolmaesumi +11 more
TL;DR: A deep convolutional neural network model, trained on a large set of samples, was developed for scoring apical four-chamber echo, which has the potential to facilitate the widespread use of echo at the point-of-care and enable early and timely diagnosis and treatment.
Book ChapterDOI
Quality Assessment of Echocardiographic Cine Using Recurrent Neural Networks: Feasibility on Five Standard View Planes
Amir H. Abdi,Christina Luong,Teresa Tsang,John Jue,Ken Gin,Darwin F. Yeung,Dale Hawley,Robert Rohling,Purang Abolmaesumi +8 more
TL;DR: The proposed approach calculates the quality of a given 20 frame echo sequence within 10 ms, sufficient for real-time deployment, and achieves this with a deep neural network model, with convolutional layers to extract hierarchical features from the input echo cine and recurrent layers to leverage the sequential information in theecho cine loop.
Clinical Research Right Atrial Volume Is Superior to Left Atrial Volume for Prediction of Atrial Fibrillation Recurrence After Direct Current Cardioversion
TL;DR: RAVI is superior to LAVI for the prediction of AF recurrence at 6 months after DCCV, and best accuracy for LAVI was ≥ 48 mL/m(2), while RAVI had superior predictive ability.
Book ChapterDOI
Deep Residual Recurrent Neural Networks for Characterisation of Cardiac Cycle Phase from Echocardiograms
Fatemeh Taheri Dezaki,Neeraj Dhungel,Amir H. Abdi,Christina Luong,Teresa Tsang,John Jue,Ken Gin,Dale Hawley,Robert Rohling,Purang Abolmaesumi +9 more
TL;DR: This work proposes to combine deep residual neural networks (ResNets), which extract the hierarchical features from the individual echocardiogram frames, with recurrent neural Networks (RNNs), which model the temporal dependencies between sequential frames, to create a new deep neural networks architecture.
Proceedings ArticleDOI
Designing lightweight deep learning models for echocardiography view classification
Hooman Vaseli,Zhibin Liao,Amir H. Abdi,Hany Girgis,Hany Girgis,Delaram Behnami,Christina Luong,Fatemeh Taheri Dezaki,Neeraj Dhungel,Robert Rohling,Ken Gin,Ken Gin,Purang Abolmaesumi,Teresa Tsang,Teresa Tsang +14 more
TL;DR: This paper presents an approach based on knowledge distillation to obtain a highly accurate lightweight deep learning model for classification of 12 standard echocardiography views, which could be used to build fast mobile applications for real-time point-of-care ultrasound diagnosis.