Erik Smistad

According to our database, Erik Smistad authored at least 23 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Toward Robust Cardiac Segmentation Using Graph Convolutional Networks.

Gilles Van De Vyver, Sarina Thomas, Guy Ben-Yosef, Sindre Hellum Olaisen, Håvard Dalen, Lasse Løvstakken, Erik Smistad

IEEE Access, 2024

2023

Immunohistochemistry guided segmentation of benign epithelial cells, in situ lesions, and invasive epithelial cells in breast cancer slides.

Maren Høibø, André Pedersen, Vibeke Grotnes Dale, Sissel Marie Berget, Borgny Ytterhus, Cecilia Lindskog, Elisabeth Wik, Lars A. Akslen, Ingerid Reinertsen, Erik Smistad, Marit Valla

CoRR, 2023

Towards Robust Cardiac Segmentation using Graph Convolutional Networks.

Gilles Van De Vyver, Sarina Thomas, Guy Ben-Yosef, Sindre Hellum Olaisen, Håvard Dalen, Lasse Løvstakken, Erik Smistad

CoRR, 2023

2021

Myocardial Function Imaging in Echocardiography Using Deep Learning.

Andreas Østvik, Ivar Mjåland Salte, Erik Smistad, Thuy Mi Nguyen, Daniela Melichova, Harald Brunvand, Kristina Haugaa, Thor Edvardsen, Bjørnar Grenne, Lasse Løvstakken

IEEE Trans. Medical Imaging, 2021

Hybrid guiding: A multi-resolution refinement approach for semantic segmentation of gigapixel histopathological images.

André Pedersen, Erik Smistad, Tor V. Rise, Vibeke G. Dale, Henrik Sahlin Pettersen, Tor-Arne S. Nordmo, David Bouget, Ingerid Reinertsen, Marit Valla

CoRR, 2021

Code-free development and deployment of deep segmentation models for digital pathology.

Henrik Sahlin Pettersen, Ilya Belevich, Elin Synnøve Røyset, Erik Smistad, Eija Jokitalo, Ingerid Reinertsen, Ingunn Bakke, André Pedersen

CoRR, 2021

FastPathology: An Open-Source Platform for Deep Learning-Based Research and Decision Support in Digital Pathology.

André Pedersen, Marit Valla, Anna M. Bofin, Javier Pérez de Frutos, Ingerid Reinertsen, Erik Smistad

IEEE Access, 2021

FAST: A framework for high-performance medical image computing and visualization.

Erik Smistad

Proceedings of the IWOCL'21: International Workshop on OpenCL, Munich Germany, April, 2021, 2021

2020

LU-Net: a multi-task network to improve the robustness of segmentation of left ventriclular structures by deep learning in 2D echocardiography.

Sarah Leclerc, Erik Smistad, Andreas Østvik, Frederic Cervenansky, Florian Espinosa, Torvald Espeland, Erik Andreas Rye Berg, Thomas Grenier, Carole Lartizien, Pierre-Marc Jodoin, Lasse Løvstakken, Olivier Bernard

CoRR, 2020

2019

Deep Learning for Segmentation Using an Open Large-Scale Dataset in 2D Echocardiography.

Sarah Leclerc, Erik Smistad, João Pedrosa, Andreas Østvik, Frederic Cervenansky, Florian Espinosa, Torvald Espeland, Erik Andreas Rye Berg, Pierre-Marc Jodoin, Thomas Grenier, Carole Lartizien, Jan D'hooge, Lasse Løvstakken, Olivier Bernard

IEEE Trans. Medical Imaging, 2019

High Performance Neural Network Inference, Streaming, and Visualization of Medical Images Using FAST.

Erik Smistad, Andreas Østvik, André Pedersen

IEEE Access, 2019

2018

Automatic Myocardial Strain Imaging in Echocardiography Using Deep Learning.

Andreas Østvik, Erik Smistad, Torvald Espeland, Erik Andreas Rye Berg, Lasse Løvstakken

Proceedings of the Deep Learning in Medical Image Analysis - and - Multimodal Learning for Clinical Decision Support, 2018

2016

Real-Time Automatic Artery Segmentation, Reconstruction and Registration for Ultrasound-Guided Regional Anaesthesia of the Femoral Nerve.

Erik Smistad, Frank Lindseth

IEEE Trans. Medical Imaging, 2016

Standardized Evaluation System for Left Ventricular Segmentation Algorithms in 3D Echocardiography.

Olivier Bernard, Johan G. Bosch, Brecht Heyde, Martino Alessandrini, Daniel Barbosa, Sorina Camarasu-Pop, Frederic Cervenansky, Sébastien Valette, Oana Mirea, Michel Bernier, Pierre-Marc Jodoin, Jaime Santo Domingos, Richard V. Stebbing, Kevin Keraudren, Ozan Oktay, Jose Caballero, Wei Shi, Daniel Rueckert, Fausto Milletari, Seyed-Ahmad Ahmadi, Erik Smistad, Frank Lindseth, Maartje van Stralen, Chen Wang, Örjan Smedby, Erwan Donal, Mark Monaghan, Alex Papachristidis, Marcel L. Geleijnse, Elena Galli, Jan D'hooge

IEEE Trans. Medical Imaging, 2016

Multigrid gradient vector flow computation on the GPU.

Erik Smistad, Frank Lindseth

J. Real Time Image Process., 2016

Vessel Detection in Ultrasound Images Using Deep Convolutional Neural Networks.

Erik Smistad, Lasse Løvstakken

Proceedings of the Deep Learning and Data Labeling for Medical Applications, 2016

2015

Medical image segmentation on GPUs - A comprehensive review.

Erik Smistad, Thomas L. Falch, Mohammadmehdi Bozorgi, Anne C. Elster, Frank Lindseth

Medical Image Anal., 2015

Real-time gradient vector flow on GPUs using OpenCL.

Erik Smistad, Anne C. Elster, Frank Lindseth

J. Real Time Image Process., 2015

FAST: framework for heterogeneous medical image computing and visualization.

Erik Smistad, Mohammadmehdi Bozorgi, Frank Lindseth

Int. J. Comput. Assist. Radiol. Surg., 2015

Automatic Real-time Annotation of Important Landmarks in Ultrasound-Guided Femoral Nerve Blocks.

Frank Lindseth, Linda Leidig, Erik Smistad

Proceedings of the Eurographics Workshop on Visual Computing for Biology and Medicine, 2015

2014

Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study.

Rina Dewi Rudyanto, Sjoerd Kerkstra, Eva M. van Rikxoort, Catalin I. Fetita, Pierre-Yves Brillet, Christophe Lefevre, Wenzhe Xue, Xiangjun Zhu, Jianming Liang, Ilkay Öksüz, Devrim Ünay, Kamuran Kadipasaoglu, Raúl San José Estépar, James C. Ross, George R. Washko, Juan-Carlos Prieto, Marcela Hernández Hoyos, Maciej Orkisz, Hans Meine, Markus Hüllebrand, Christina Stöcker, Fernando López-Mir, Valery Naranjo, Eliseo Villanueva, Marius Staring, Changyan Xiao, Berend C. Stoel, Anna Fabijanska, Erik Smistad

Medical Image Anal., 2014

GPU accelerated segmentation and centerline extraction of tubular structures from medical images.

Erik Smistad, Anne C. Elster, Frank Lindseth

Int. J. Comput. Assist. Radiol. Surg., 2014

A New Tube Detection Filter for Abdominal Aortic Aneurysms.

Erik Smistad, Reidar Brekken, Frank Lindseth

Proceedings of the Abdominal Imaging. Computational and Clinical Applications, 2014