Örjan Smedby


Professor of medical image processing and visualization, Department of Biomedical Engineering and Health Systems
KTH Royal Institute of Technology


Medical image processing
Machine learning
Medical visualization


Google Scholar Citations


Google Scholar h-index


Google Scholar i10-index


  • Image quality and pathology assessment in CT Urography: when is the low-dose series sufficient?
    B Kataria, JN Althn, Smedby, A Persson, H Skjer, M Sandborg
    BMC medical imaging 19 (1), 64 2019

  • Normal Appearance Autoencoder for Lung Cancer Detection and Segmentation
    M Astaraki, I Toma-Dasu, Smedby, C Wang
    International Conference on Medical Image Computing and Computer-Assisted 2019

  • A Two-Stage U-Net Algorithm for Segmentation of Nuclei in H&E-Stained Tissues
    A Mahbod, G Schaefer, I Ellinger, R Ecker, Smedby, C Wang
    European Congress on Digital Pathology, 75-82 2019

  • OC-0406 Early survival prediction in non-small cell lung cancer with PET/CT size aware longitudinal pattern
    M Astaraki, C Wang, G Buizza, I Toma-Dasu, M Lazzeroni, Smedby
    Radiotherapy and Oncology 133, S208-S209 2019

  • Early survival prediction in non-small cell lung cancer from PET/CT images using an intra-tumor partitioning method
    M Astaraki, C Wang, G Buizza, I Toma-Dasu, M Lazzeroni, Smedby
    Physica Medica 60, 58-65 2019

  • Automatic rat brain segmentation from MRI using statistical shape models and random forest
    S Bendazzoli, I Brusini, P Damberg, Smedby, L Andersson, C Wang
    Medical Imaging 2019: Image Processing 10949, 109492O 2019

  • Simultaneous MR knee image segmentation and bias field correction using deep learning and partial convolution
    F Wan, Smedby, C Wang
    Medical Imaging 2019: Image Processing 10949, 1094909 2019

  • Evaluation of Algorithms for Multi-Modality Whole Heart Segmentation: An Open-Access Grand Challenge
    X Zhuang, L Li, C Payer, D Stern, M Urschler, MP Heinrich, J Oster, ...
    arXiv preprint arXiv:1902.07880 2019

  • Early tumor response prediction for lung cancer patients using novel longitudinal pattern features from sequential PET/CT image scans
    G Buizza, I Toma-Dasu, M Lazzeroni, C Paganelli, M Riboldi, Y Chang, ...
    Physica Medica 54, 21-29 2018

  • Voxel-Wise Clustering of Tractography Data for Building Atlases of Local Fiber Geometry
    I Brusini, D Jrgens, Smedby, R Moreno
    International Conference on Medical Image Computing and Computer-Assisted 2018

  • Pelvis segmentation using multi-pass U-Net and iterative shape estimation
    C Wang, B Connolly, PF de Oliveira Lopes, AF Frangi, Smedby
    International Workshop on Computational Methods and Clinical Applications in 2018

  • Changes in brain architecture are consistent with altered fear processing in domestic rabbits
    I Brusini, M Carneiro, C Wang, CJ Rubin, H Ring, S Afonso, ...
    Proceedings of the National Academy of Sciences 115 (28), 7380-7385 2018

  • Direct estimation of human trabecular bone stiffness using cone beam computed tomography
    E Klintstrm, B Klintstrm, D Pahr, TB Brismar, Smedby, R Moreno
    Oral surgery, oral medicine, oral pathology and oral radiology 126 (1), 72-82 2018

  • Breast cancer histological image classification using fine-tuned deep network fusion
    A Mahbod, I Ellinger, R Ecker, Smedby, C Wang
    International Conference Image Analysis and Recognition, 754-762 2018

  • Convolutional neural network-based image enhancement for x-ray percutaneous coronary intervention
    M Pavoni, Y Chang, S Park, Smedby
    Journal of Medical Imaging 5 (2), 024006 2018

  • Assessment of image quality in abdominal CT: potential dose reduction with model-based iterative reconstruction
    B Kataria, JN Althn, Smedby, A Persson, H Skjer, M Sandborg
    European radiology 28 (6), 2464-2473 2018

  • Quantitative measurements versus receiver operating characteristics and visual grading regression in CT images reconstructed with iterative reconstruction: a phantom study
    K Jensen, HK Andersen, Smedby, BH sters, A Aarsnes, A Tingberg, ...
    Academic radiology 25 (4), 509-518 2018

  • Learning a single step of streamline tractography based on neural networks
    D Jrgens, Smedby, R Moreno
    Computational Diffusion MRI, 103-116 2018

  • Automatic brain segmentation using artificial neural networks with shape context
    A Mahbod, M Chowdhury, Smedby, C Wang
    Pattern Recognition Letters 101, 74-79 2018

  • Image denoising with convolutional neural networks for percutaneous transluminal coronary angioplasty
    M Pavoni, Y Chang, Smedby
    European Congress on Computational Methods in Applied Sciences and 2017


  • Standardized evaluation methodology and reference database for evaluating coronary artery centerline extraction algorithms
    M Schaap, CT Metz, T van Walsum, AG van der Giessen, AC Weustink, ...
    Medical image analysis 13 (5), 701-714 2009
    Citations: 285

  • Web‐based interactive 3D visualization as a tool for improved anatomy learning
    H Petersson, D Sinkvist, C Wang, Smedby
    Anatomical sciences education 2 (2), 61-68 2009
    Citations: 189

  • Iodinated contrast opacification gradients in normal coronary arteries imaged with prospectively ECG-gated single heart beat 320-detector row computed tomography
    ML Steigner, D Mitsouras, AG Whitmore, HJ Otero, C Wang, O Buckley, ...
    Circulation: Cardiovascular Imaging 3 (2), 179-186 2010
    Citations: 152

  • Contrast-enhanced magnetic resonance cholangiography with Gd-BOPTA and Gd-EOB-DTPA in healthy subjects
    N Dahlstrm, A Persson, N Albiin, Smedby, TB Brismar
    Acta Radiologica 48 (4), 362-368 2007
    Citations: 112

  • MRBrainS challenge: online evaluation framework for brain image segmentation in 3T MRI scans
    AM Mendrik, KL Vincken, HJ Kuijf, M Breeuwer, WH Bouvy, J De Bresser, ...
    Computational intelligence and neuroscience 2015, 1 2015
    Citations: 107

  • Advanced 3D visualization in student-centred medical education
    C Siln, S Wirell, J Kvist, E Nylander, Smedby
    Medical teacher 30 (5), e115-e124 2008
    Citations: 106

  • A novel infraclavicular brachial plexus block: the lateral and sagittal technique, developed by magnetic resonance imaging studies
    Klaastad, HJ Smith, Smedby, EH Winther-Larssen, P Brodal, ...
    Anesthesia & Analgesia 98 (1), 252-256 2004
    Citations: 99

  • Distribution of Local Anesthetic in Axillary Brachial Plexus BlockA Clinical and Magnetic Resonance Imaging Study
    Klaastad, Smedby, GE Thompson, T Tillung, PK Hol, JS Rtnes, ...
    Anesthesiology: The Journal of the American Society of Anesthesiologists 96 2002
    Citations: 90

  • Two-dimensional tortuosity of the superficial femoral artery in early atherosclerosis
    Smedby, N Hgman, S Nilsson, U Erikson, AG Olsson, G Walldius
    Journal of vascular research 30 (4), 181-191 1993
    Citations: 80

  • Quantifying differences in hepatic uptake of the liver specific contrast agents Gd-EOB-DTPA and Gd-BOPTA: a pilot study
    OD Leinhard, N Dahlstrm, J Kihlberg, P Sandstrm, TB Brismar, ...
    European radiology 22 (3), 642-653 2012
    Citations: 73

  • Tortuosity and atherosclerosis in the femoral artery: what is cause and what is effect?
    Smedby, L Bergstrand
    Annals of biomedical engineering 24 (4), 474 1996
    Citations: 73

  • Do plaques grow upstream or downstream? An angiographic study in the femoral artery
    O Smedby
    Arteriosclerosis, thrombosis, and vascular biology 17 (5), 912-918 1997
    Citations: 72

  • Visual grading regression: analysing data from visual grading experiments with regression models
    Smedby, M Fredrikson
    The British journal of radiology 83 (993), 767-775 2010
    Citations: 69

  • Quantitative abdominal fat estimation using MRI
    OD Leinhard, A Johansson, J Rydell, O Smedby, F Nystrom, P Lundberg, ...
    2008 19th International Conference on Pattern Recognition, 1-4 2008
    Citations: 64

  • Liver vessel enhancement by Gd-BOPTA and Gd-EOB-DTPA: a comparison in healthy volunteers
    TB Brismar, N Dahlstrm, N Edsborg, A Persson, Smedby, N Albiin
    Acta radiologica 50 (7), 709-715 2009
    Citations: 62

  • Separation of advanced from mild fibrosis in diffuse liver disease using 31P magnetic resonance spectroscopy
    B Noren, O Dahlqvist, P Lundberg, S Almer, S Kechagias, M Ekstedt, ...
    European journal of radiology 66 (2), 313-320 2008
    Citations: 62

  • Separation of advanced from mild hepatic fibrosis by quantification of the hepatobiliary uptake of Gd-EOB-DTPA
    B Norn, MF Forsgren, OD Leinhard, N Dahlstrm, J Kihlberg, T Romu, ...
    European radiology 23 (1), 174-181 2013
    Citations: 61

  • Synthetic MRI of the brain in a clinical setting
    I Blystad, JBM Warntjes, O Smedby, AM Landtblom, P Lundberg, ...
    Acta radiologica 53 (10), 1158-1163 2012
    Citations: 60

  • Measures of continuity of care: A register-based correlation study
    Smedby, G Eklund, EA Eriksson, B Smedby
    Medical care, 511-518 1986
    Citations: 59

  • MRI‐guided celiac plexus block
    PK Hol, G Kvarstein, O Viken, Smedby, TI Tnnessen
    Journal of Magnetic Resonance Imaging: An Official Journal of the 2000
    Citations: 56