Blar i SINTEF Digital på tidsskrift "Proceedings - IEEE Ultrasonics Symposium"

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    • Fully automatic real-time ejection fraction and MAPSE measurements in 2D echocardiography using deep neural networks 

      Smistad, Erik; Østvik, Andreas; Salte, Ivar Mjåland; Leclerc, Sarah; Bernard, Olivier; Løvstakken, Lasse (Journal article; Peer reviewed, 2018)
      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 ...

    • The Effect of Sonication on Extravasation and Distribution of Nanoparticles and Dextrans in Tumor Tissue Imaged by Multiphoton Microscopy 

      Yemane, Petros Tesfamichael; Åslund, Andreas; Sæterbø, Kristin Grendstad; Bjørkøy, Astrid; Snipstad, Sofie; van Wamel, Annemieke; Berg, Sigrid; Mørch, Ýrr Asbjørg; Hansen, Rune; Angelsen, Bjørn Atle Johan; Davies, Catharina de Lange (Journal article; Peer reviewed, 2018)
      Ultrasound (US)and systemic administration of microbubbles (MBs)have been shown to improve the delivery of drugs and nanoparticles (NPs)to tumor tissue. A better understanding of the mechanisms is crucial for effective ...

    • Ultrasonic focusing through a steel layer for acoustic imaging 

      Talberg, Andreas Sørbrøden; Dong, Hefeng; Johansen, Tonni Franke; Måsøy, Svein-Erik; Brekke, Svein; Rommetveit, Tarjei (Journal article; Peer reviewed, 2018)
      Ultrasonic tools are being used for imaging in a large variety of fields, spanning from medical applications in a hospital to applications deep down in oil and gas wells. When applying ultrasonic imaging techniques to image ...

    • Ultrasound speckle reduction using generative adversial networks 

      Dietrichson, Fabian Sødal; Smistad, Erik; Østvik, Andreas; Løvstakken, Lasse (Journal article; Peer reviewed, 2018)
      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 ...