Background and activities

 

PhD candidate at the Department of Circulation and Medical Imaging financed by CIUS. Current research projects involve automatic methods for analysing medical images using machine learning methodology. The main application is cardiac ultrasound imaging, where the goal is to develop good diagnostic tools and improve workflow in the clinic.

 

Research interests

  • Ultrasound, and other medical imaging modalities

  • Machine learning with emphasis on deep neural networks

  • Robotics and machine vision in medical intervention

 

Background

Master of Science (MSc) in physics and mathematics with specialization in biophysics and medical technology. Master thesis on the topic of Robot Control in Image-Guided Intervention.

Scientific, academic and artistic work

Displaying a selection of activities. See all publications in the database

Journal publications

Others

  • Østvik, Andreas; Smistad, Erik; Løvstakken, Lasse. (2018) Deep learning for ultrasound image classification and segmentation. Myocardial velocity and deformation imaging ; Leuven. 2018-02-08 - 2018-02-09.
  • Smistad, Erik; Østvik, Andreas; Haugen, Bjørn Olav; Løvstakken, Lasse. (2017) 2D Left ventricle segmentation using deep learning. International Ultrasonics Symposium (IUS) ; Washington DC. 2017-09-06 - 2017-09-09.
  • Østvik, Andreas; Smistad, Erik; Aase, Svein Arne; Haugen, Bjørn Olav; Løvstakken, Lasse. (2017) Real-Time Classification of Standard Cardiac Views in Echocardiography using Neural Networks. IEEE International Ultrasonics Symposium ; Washington DC. 2017-09-06 - 2017-09-09.