Erik Smistad
About
Working 50% as a post doc at the CIUS project and 50% as a researcher at SINTEF Medical Technology.
Primary research interests
- Image segmentation
- Machine learning and neural networks
- Parallel and GPU processing
- Ultrasound
If you are interested in the same topics, please don't hesitate to contact me at erik.smistad@ntnu.no.
See my personal webpage www.eriksmistad.no for more information about my research.
Publications
2017
-
Smistad, Erik;
Iversen, Daniel Høyer;
Leidig, Linda;
Bakeng, Janne Beate Lervik;
Johansen, Kaj Fredrik;
Lindseth, Frank.
(2017)
Automatic Segmentation and Probe Guidance for Real-Time Assistance of Ultrasound-Guided Femoral Nerve Blocks.
Ultrasound in Medicine and Biology
Academic article
2016
-
Smistad, Erik;
Løvstakken, Lasse.
(2016)
Vessel detection in ultrasound images using deep convolutional neural networks.
Lecture Notes in Computer Science (LNCS)
Academic article
-
Grønli, Thomas;
Smistad, Erik;
Nyrnes, Siri Ann;
Gomez, Alberto;
Løvstakken, Lasse.
(2016)
Reconstruction of In Vivo Flow Velocity Fields Based On a Rapid Ultrasound Image Segmentation and B-spline Regularization Framework.
Proceedings - IEEE Ultrasonics Symposium
Academic article
-
Smistad, Erik;
Lindseth, Frank.
(2016)
Real-Time Automatic Artery Segmentation, Reconstruction and Registration for Ultrasound-Guided Regional Anaesthesia of the Femoral Nerve.
IEEE Transactions on Medical Imaging
Academic article
2015
-
Smistad, Erik;
Elster, Anne C.;
Lindseth, Frank.
(2015)
Real-time gradient vector flow on GPUs using OpenCL.
Journal of Real-Time Image Processing
Academic article
-
Smistad, Erik;
Bozorgi, Mohammadmehdi;
Lindseth, Frank.
(2015)
FAST: framework for heterogeneous medical image computing and visualization.
International Journal of Computer Assisted Radiology and Surgery
Academic article
-
Smistad, Erik;
Falch, Thomas Løfsgaard;
Bozorgi, Mohammadmehdi;
Elster, Anne C.;
Lindseth, Frank.
(2015)
Medical image segmentation on GPUs - A comprehensive review.
Medical Image Analysis
Academic literature review
-
Smistad, Erik.
(2015)
Medical Image Segmentation for Improved Surgical Navigation.
Doktoravhandlinger ved NTNU (236)
Doctoral dissertation
2014
-
Smistad, Erik;
Brekken, Reidar;
Lindseth, Frank.
(2014)
A new tube detection filter for abdominal aortic aneurysms.
Lecture Notes in Computer Science (LNCS)
Academic article
-
Smistad, Erik;
Elster, Anne C.;
Lindseth, Frank.
(2014)
GPU accelerated segmentation and centerline extraction of tubular structures from medical images.
International Journal of Computer Assisted Radiology and Surgery
Academic article
-
Smistad, Erik;
Lindseth, Frank.
(2014)
Multigrid gradient vector flow computation on the GPU.
Journal of Real-Time Image Processing
Academic article
2012
-
Smistad, Erik;
Elster, Anne C.;
Lindseth, Frank.
(2012)
GPU-Based Airway Segmentation and Centerline Extraction for Image Guided Bronchoscopy.
NIKT: Norsk IKT-konferanse for forskning og utdanning
Academic article
-
Smistad, Erik;
Elster, Anne C.;
Lindseth, Frank.
(2012)
Real-Time Surface Extraction and Visualization of Medical Images using OpenCL and GPUs.
NIKT: Norsk IKT-konferanse for forskning og utdanning
Academic article
Journal publications
-
Smistad, Erik;
Iversen, Daniel Høyer;
Leidig, Linda;
Bakeng, Janne Beate Lervik;
Johansen, Kaj Fredrik;
Lindseth, Frank.
(2017)
Automatic Segmentation and Probe Guidance for Real-Time Assistance of Ultrasound-Guided Femoral Nerve Blocks.
Ultrasound in Medicine and Biology
Academic article
-
Smistad, Erik;
Løvstakken, Lasse.
(2016)
Vessel detection in ultrasound images using deep convolutional neural networks.
Lecture Notes in Computer Science (LNCS)
Academic article
-
Grønli, Thomas;
Smistad, Erik;
Nyrnes, Siri Ann;
Gomez, Alberto;
Løvstakken, Lasse.
(2016)
Reconstruction of In Vivo Flow Velocity Fields Based On a Rapid Ultrasound Image Segmentation and B-spline Regularization Framework.
Proceedings - IEEE Ultrasonics Symposium
Academic article
-
Smistad, Erik;
Lindseth, Frank.
(2016)
Real-Time Automatic Artery Segmentation, Reconstruction and Registration for Ultrasound-Guided Regional Anaesthesia of the Femoral Nerve.
IEEE Transactions on Medical Imaging
Academic article
-
Smistad, Erik;
Elster, Anne C.;
Lindseth, Frank.
(2015)
Real-time gradient vector flow on GPUs using OpenCL.
Journal of Real-Time Image Processing
Academic article
-
Smistad, Erik;
Bozorgi, Mohammadmehdi;
Lindseth, Frank.
(2015)
FAST: framework for heterogeneous medical image computing and visualization.
International Journal of Computer Assisted Radiology and Surgery
Academic article
-
Smistad, Erik;
Falch, Thomas Løfsgaard;
Bozorgi, Mohammadmehdi;
Elster, Anne C.;
Lindseth, Frank.
(2015)
Medical image segmentation on GPUs - A comprehensive review.
Medical Image Analysis
Academic literature review
-
Smistad, Erik;
Brekken, Reidar;
Lindseth, Frank.
(2014)
A new tube detection filter for abdominal aortic aneurysms.
Lecture Notes in Computer Science (LNCS)
Academic article
-
Smistad, Erik;
Elster, Anne C.;
Lindseth, Frank.
(2014)
GPU accelerated segmentation and centerline extraction of tubular structures from medical images.
International Journal of Computer Assisted Radiology and Surgery
Academic article
-
Smistad, Erik;
Lindseth, Frank.
(2014)
Multigrid gradient vector flow computation on the GPU.
Journal of Real-Time Image Processing
Academic article
-
Smistad, Erik;
Elster, Anne C.;
Lindseth, Frank.
(2012)
GPU-Based Airway Segmentation and Centerline Extraction for Image Guided Bronchoscopy.
NIKT: Norsk IKT-konferanse for forskning og utdanning
Academic article
-
Smistad, Erik;
Elster, Anne C.;
Lindseth, Frank.
(2012)
Real-Time Surface Extraction and Visualization of Medical Images using OpenCL and GPUs.
NIKT: Norsk IKT-konferanse for forskning og utdanning
Academic article
Report
-
Smistad, Erik.
(2015)
Medical Image Segmentation for Improved Surgical Navigation.
Doktoravhandlinger ved NTNU (236)
Doctoral dissertation
Outreach
2014
-
Academic lectureSmistad, Erik; Lindseth, Frank. (2014) Real-time Tracking of the Left Ventricle in 3D Ultrasound Using Kalman Filter and Mean Value Coordinates. Proceedings MICCAI Challenge on Echocardiographic Three-Dimensional Ultrasound Segmentation (CETUS) , Boston 2014-09-14 - 2014-09-18