Lasse Løvstakken
Background and activities
My research interests is targeted towards medical ultrasound imaging, a method where echoes from high-frequency sound waves emitted into the body can be used to make images and measure properties of tissue and blood flow. Ultrasound imaging technology has had a remarkable development in recent years, providing a basis for clearer images that can be used to obtain a more certain medical diagnosis in the future healthcare.
Follow this link to read more about one of my on-going research projects where we are developing and evaluating 3D ultrasound imaging of blood flow in the hearts of children and adults: http://blog.medisin.ntnu.no/3d-ultralydbilder-av-blodstrom-kan-gi-bedre-forstaelse-av-hjertesykdom/
Scientific, academic and artistic work
A selection of recent journal publications, artistic productions, books, including book and report excerpts. See all publications in the database
Journal publications
- (2020) Blood Speckle-Tracking Based on High–Frame Rate Ultrasound Imaging in Pediatric Cardiology. Journal of the American Society of Echocardiography. vol. 33 (4).
- (2020) Real-Time Automatic Ejection Fraction and Foreshortening Detection Using Deep Learning. IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.
- (2020) Assessment of Diastolic Intraventricular Pressure Gradients in Children by Blood Speckle Tracking. A Feasibility Study. Journal of the American Society of Echocardiography. vol. 33 (3).
- (2020) Automatic interpretation of cement evaluation logs from cased boreholes using supervised deep neural networks. Journal of Petroleum Science and Engineering. vol. 195.
- (2019) Data Adaptive 2-D Tracking Doppler for High-Resolution Spectral Estimation. IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control. vol. 67 (1).
- (2019) RU-Net: A refining segmentation network for 2D echocardiography. Proceedings - IEEE Ultrasonics Symposium. vol. 2019-October.
- (2019) Deep Learning for Segmentation using an Open Large-Scale Dataset in 2D Echocardiography. IEEE Transactions on Medical Imaging. vol. 38 (9).
- (2019) A Direct Measurement of Inter-Element Cross-Talk in Ultrasound Arrays. Proceedings - IEEE Ultrasonics Symposium. vol. 2019-October.
- (2019) High frame rate color flow echocardiography: A comparison of different imaging approaches. Journal of the Acoustical Society of America. vol. 146 (4).
- (2019) Clutter Filter Wave Imaging. IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control. vol. 66 (9).
- (2019) Segmentation of apical long axis, four- and two-chamber views using deep neural networks. Proceedings - IEEE Ultrasonics Symposium. vol. 2019-October.
- (2019) Ventriculo-arterial interaction may be assessed by Oscillatory Power Fraction. Clinical Physiology and Functional Imaging. vol. 39 (5).
- (2018) Ultrasound speckle reduction using generative adversial networks. Proceedings - IEEE Ultrasonics Symposium. vol. 2018-October:8579764.
- (2018) Detection of Cardiac Events in Echocardiography using 3D Convolutional Recurrent Neural Networks. Proceedings - IEEE Ultrasonics Symposium.
- (2018) A fast 4D B-spline framework for model-based reconstruction and regularization in vector flow imaging. Proceedings - IEEE Ultrasonics Symposium. vol. 2018-October.
- (2018) Automatic intraoperative estimation of blood flow direction during neurosurgical interventions. International Journal of Computer Assisted Radiology and Surgery. vol. 13 (5).
- (2018) Quantitative Doppler analysis using conventional color flow imaging acquisitions. IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control. vol. 65 (5).
- (2018) Deep learning applied to multi-structure segmentation in 2D echocardiography: A preliminary investigation of the required database size. Proceedings - IEEE Ultrasonics Symposium.
- (2018) Spatial and temporal adaptive FIR clutter filtering. Proceedings - IEEE Ultrasonics Symposium. vol. 2018-October.
- (2018) Fully automatic real-time ejection fraction and MAPSE measurements in 2D echocardiography using deep neural networks. Proceedings - IEEE Ultrasonics Symposium.