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Andreas Østvik

Master of Science

Andreas Østvik

Master of Science

Andreas Østvik
Phone: 977 98 820
Department: Health Research
Office: Trondheim

Publications and responsibilities

Publication
https://www.sintef.no/en/publications/publication/?pubid=CRIStin+1627892

Generative adversial networks (GANs) have shown its ability to create realistic and accurate image-to-image transformation. The goal of this work was to investigate whether deep convolutional GANs can learn to perform advanced ultrasound speckle reduction in real-time. The GAN was trained using a da...

Authors Dietrichson Fabian Sødal Smistad Erik Østvik Andreas Løvstakken Lasse
Year 2018
Type Journal publication
Publication
https://www.sintef.no/en/publications/publication/?pubid=CRIStin+1627891

Cardiac ultrasound measurements such as left ventricular volume, ejection fraction (EF) and mitral annular plane systolic excursion (MAPSE) are time consuming and highly observer dependent. In this work, we investigate if deep neural networks can be used to fully automate cardiac ultrasound measurem...

Authors Smistad Erik Østvik Andreas Salte Ivar Mjåland Leclerc Sarah Bernard Olivier Løvstakken Lasse
Year 2018
Type Journal publication
Publication
https://www.sintef.no/en/publications/publication/?pubid=CRIStin+1625771

Transthoracic echocardiography examinations are usually performed according to a protocol comprising different probe postures providing standard views of the heart. These are used as a basis when assessing cardiac function, and it is essential that the morphophysiological representations are correct...

Authors Østvik Andreas Smistad Erik Aase Svein Arne Haugen Bjørn Olav Løvstakken Lasse
Year 2018
Type Journal publication
Publication
https://www.sintef.no/en/publications/publication/?pubid=CRIStin+1618327

Recent studies in the field of deep learning suggest that motion estimation can be treated as a learnable problem. In this paper we propose a pipeline for functional imaging in echocardiography consisting of four central components, (i) classification of cardiac view, (ii) semantic partitioning of t...

Authors Østvik Andreas Smistad Erik Espeland Torvald Berg Erik Andreas Rye Løvstakken Lasse
Year 2018
Type Journal publication