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Ilkay Öksüz | Julia A. Schnabel | James R. Clough | Andrew P. King | Bram Ruijsink | Esther Puyol-Antón | J. Schnabel | A. King | Ilkay Öksüz | B. Ruijsink | E. Puyol-Antón | J. Clough
[1] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[2] Daniel Rueckert,et al. Learning Interpretable Anatomical Features Through Deep Generative Models: Application to Cardiac Remodeling , 2018, MICCAI.
[3] Ben Glocker,et al. Automated cardiovascular magnetic resonance image analysis with fully convolutional networks , 2017, Journal of Cardiovascular Magnetic Resonance.
[4] P. Matthews,et al. UK Biobank’s cardiovascular magnetic resonance protocol , 2015, Journal of Cardiovascular Magnetic Resonance.
[5] Been Kim,et al. Sanity Checks for Saliency Maps , 2018, NeurIPS.
[6] H. H. Madden. Comments on the Savitzky-Golay convolution method for least-squares-fit smoothing and differentiation of digital data , 1976 .
[7] Cynthia Rudin,et al. Please Stop Explaining Black Box Models for High Stakes Decisions , 2018, ArXiv.
[8] Martin Wattenberg,et al. Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) , 2017, ICML.
[9] Konstantinos Kamnitsas,et al. Anatomically Constrained Neural Networks (ACNNs): Application to Cardiac Image Enhancement and Segmentation , 2017, IEEE Transactions on Medical Imaging.
[10] Cynthia Rudin,et al. Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead , 2018, Nature Machine Intelligence.
[11] Rama Chellappa,et al. Visual Domain Adaptation: A survey of recent advances , 2015, IEEE Signal Processing Magazine.
[12] A. Savitzky,et al. Smoothing and Differentiation of Data by Simplified Least Squares Procedures. , 1964 .
[13] Seth Flaxman,et al. EU regulations on algorithmic decision-making and a "right to explanation" , 2016, ArXiv.
[14] Andrew Zisserman,et al. Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps , 2013, ICLR.
[15] Arvind Satyanarayan,et al. The Building Blocks of Interpretability , 2018 .
[16] Martin Wattenberg,et al. TCAV: Relative concept importance testing with Linear Concept Activation Vectors , 2018 .
[17] Xin Yang,et al. Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved? , 2018, IEEE Transactions on Medical Imaging.
[18] Wenjia Bai,et al. Fully Automated, Quality-Controlled Cardiac Analysis From CMR: Validation and Large-Scale Application to Characterize Cardiac Function , 2019, JACC. Cardiovascular imaging.