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Search results for biblio_type:Proceedings, non-refereed
Filters: 1 is biblio_type:Proceedings, refereed and 2 is biblio_type:Manuals and 3 is biblio_year:2019 and 4 is biblio_year:1988 and 5 is field_publication_state:18 and 6 is biblio_year:2018 and 7 is 8009 and 8 is field_research_area:590 and Author is Thomas de Lange  [Reset Search]
2021
D. Jha, S. Ali, S. Hicks, V. Thambawita, H. Borgli, P. H. Smedsrud, T. de Lange, K. Pogorelov, X. Wang, P. Harzig et al. "A comprehensive analysis of classification methods in gastrointestinal endoscopy imaging." Medical Image Analysis (2021).PDF icon 2.pdf (3.22 MB)
D. Jha, P. H. Smedsrud, D. Johansen, T. de Lange, H. D. Johansen, P. Halvorsen and M. Riegler. "A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time Augmentation." IEEE Journal of Biomedical and Health Informatics (2021).PDF icon 09314114.pdf (6.16 MB)
V. Thambawita, S. Hicks, J. Isaksen, M. H. Stensen, T. B. Haugen, J. Kanters, S. Parasa, T. de Lange, H. D. Johansen, D. Johansen et al. DeepSynthBody: the beginning of the end for data deficiency in medicine In The International Conference on Applied Artificial Intelligence (ICAPAI)., 2021.
D. Jha, S. Ali, K. Emanuelsen, S. Hicks, V. Thambawita, E. Garcia-Ceja, M. Riegler, T. de Lange, P. T. Schmidt, H. D. Johansen et al. Kvasir-Instrument: Diagnostic and therapeutic tool segmentation dataset in gastrointestinal endoscopy In 27th International Conference on Multimedia Modeling. MMM 2021, 2021.PDF icon mmm.pdf (648.64 KB)
D. Jha, N. K. Tomar, S. Ali, M. Riegler, H. D. Johansen, D. Johansen, T. de Lange and P. Halvorsen. NanoNet: Real-Time Polyp Segmentation in Video Capsule Endoscopy and Colonoscopy In 34th IEEE CBMS International Symposium on Computer-Based Medical Systems. IEEE, 2021.PDF icon 412100a037.pdf (789.29 KB)
2018
K. Pogorelov, O. Ostroukhova, A. Petlund, P. Halvorsen, H. Espeland, T. Kupka, T. de Lange, C. Griwodz and M. Riegler. Automatic Detection of Angiectasia: Evaluation of Deep Learning and Handcrafted Approaches In IEEE Conference on Biomedical and Health Informatics (BHI) 2018., 2018.
S. Hicks, K. Pogorelov, M. Lux, M. Jeppsson, K. R. Randel, T. de Lange, S. L. Eskeland, P. Halvorsen and M. Riegler. Comprehensible Reasoning and Automated Reporting of Medical Examinations Based on Deep Learning Analysis In Proceedings of the 9th ACM Multimedia Systems Conference. Amsterdam, Netherlands: ACM, 2018.
K. Pogorelov, O. Ostroukhova, A. Petlund, P. Halvorsen, T. de Lange, H. Espeland, T. Kupka, C. Griwodz and M. Riegler. Deep Learning and Handcrafted Feature Based Approaches for Automatic Detection of Angiectasia In 2018 IEEE Conference on Biomedical and Health Informatics (BHI). IEEE, 2018.
K. Pogorelov, O. Ostroukhova, M. Jeppsson, H. Espeland, C. Griwodz, T. de Lange, D. Johansen, M. Riegler and P. Halvorsen. Deep Learning and Hand-crafted Feature Based Approaches for Polyp Detection in Medical Videos In 31st IEEE CBMS International Symposium on Computer-Based Medical Systems. Karlstad, Sweden: IEEE, 2018.PDF icon cbms_2018_paper_163_preprint.pdf (1.61 MB)
S. Hicks, M. Riegler, K. Pogorelov, T. de Lange, K. R. Randel, K. V. Ånonsen, M. Jeppsson, P. Halvorsen and S. L. Eskeland. Dissecting Deep Neural Networks for Better Medical Image Classification and Classification Understanding In 31st IEEE CBMS International Symposium on Computer-Based Medical Systems. Karlstad, Sweden: IEEE, 2018.
K. Pogorelov, M. Riegler, P. Halvorsen, S. Hicks, K. R. Randel, D. Dang-Nguyen, M. Lux, O. Ostroukhova and T. de Lange. Medico Multimedia Task at MediaEval 2018 In Working Notes Proceedings of the MediaEval 2018 Workshop. CEUR Workshop Proceedings, 2018.PDF icon mediaeval_18_paper_63.pdf (348.1 KB)
T. de Lange, P. Halvorsen and M. Riegler. "Methodology to develop machine learning algorithms to improve performance in gastrointestinal endoscopy." World Journal of Gastroenterology 45, no. 24 (2018): 5057-5062.PDF icon wjg-24-5057.pdf (1.26 MB)
S. Hicks, M. Lux, T. de Lange, K. R. Randel, M. Jeppsson, K. Pogorelov, P. Halvorsen and M. Riegler. Mimir: An Automatic Reporting and Reasoning System for Deep Learning based Analysis in the Medical Domain In Proceedings of the 9th ACM Multimedia Systems Conference. Amsterdam, Netherlands: ACM, 2018.
T. J. D. Berstad, M. Riegler, H. Espeland, T. de Lange, P. H. Smedsrud, K. Pogorelov, H. K. Stensland and P. Halvorsen. Tradeoffs using Binary and Multiclass Neural Network Classification for Medical Multidisease Detection In 2018 IEEE International Symposium on Multimedia (ISM). IEEE, 2018.PDF icon main.pdf (807.82 KB)

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