• Artificial intelligence in the fertility clinic: status, pitfalls and possibilities 

      Riegler, Michael Alexander; Stensen, Mette Haug; Witczak, Oliwia; Andersen, Jorunn Marie; Hicks, Steven; Hammer, Hugo Lewi; Delbarre, Erwan; Halvorsen, Pål; Yazidi, Anis; Holst, Nicolai; Haugen, Trine B. (Human Reproduction;Volume 36, Issue 9, Peer reviewed; Journal article, 2021-07-29)
      In recent years, the amount of data produced in the field of assisted reproduction technology [ART] has increased exponentially. The diversity of data is large, ranging from videos to tabular data. At the same time, ...
    • Automated reporting system using deep convolutional neural network in the medical domain 

      Subedi, Matrika (MAUU;2021, Master thesis, 2021)
      Nowadays, in the healthcare sector, a massive volume of medical data sources is available. The data is growing at 153 Exabytes in 2013 and an estimated 2,314 exabytes in 2020 (Turner, Gantz et al. 2014). The medical data ...
    • A comprehensive analysis of classification methods in gastrointestinal endoscopy imaging 

      Jha, Debesh; Ali, Sharib; Hicks, Steven; Thambawita, Vajira L B; Borgli, Hanna; Smedsrud, Pia H.; de Lange, Thomas; Pogorelov, Konstantin; Wang, Xiaowei; Harzig, Philipp; Tran, Minh-Triet; Meng, Wenhua; Hoang, Trung-Hieu; Dias, Danielle; Ko, Tobey H.; Agrawal, Taruna; Ostroukhova, Olga; Khan, Zeshan; Tahir, Muhammed Atif; Liu, Yang; Chang, Yuan; Kirkerød, Mathias; Johansen, Dag; Lux, Mathias; Johansen, Håvard D.; Riegler, Michael; Halvorsen, Pål (Peer reviewed; Journal article, 2021)
      Gastrointestinal (GI) endoscopy has been an active field of research motivated by the large number of highly lethal GI cancers. Early GI cancer precursors are often missed during the endoscopic surveillance. The high missed ...
    • Explaining deep neural networks for knowledge discovery in electrocardiogram analysis 

      Hicks, Steven; Isaksen, Jonas L; Thambawita, Vajira L B; Ghouse, Jonas; Ahlberg, Gustav; Linneberg, Allan; Grarup, Niels; Strumke, Inga; Ellervik, Christina; Olesen, Morten Salling; Hansen, Torben; Graff, Claus; Holstein-Rathlou, Niels-Henrik; Halvorsen, Pål; Maleckar, Mary Margot Catherine; Riegler, Michael; Kanters, Jørgen K (Scientific Reports;11, Article number: 10949 (2021), Peer reviewed; Journal article, 2021-05-26)
      Deep learning-based tools may annotate and interpret medical data more quickly, consistently, and accurately than medical doctors. However, as medical doctors are ultimately responsible for clinical decision-making, any ...
    • HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy 

      Borgli, Hanna; Thambawita, Vajira; Smedsrud, Pia H; Hicks, Steven; Jha, Debesh; Eskeland, Sigrun Losada; Randel, Kristin Ranheim; Pogorelov, Konstantin; Lux, Mathias; Dang Nguyen, Duc Tien; Johansen, Dag; Griwodz, Carsten; Stensland, Håkon Kvale; Garcia-Ceja, Enrique; Schmidt, Peter T; Hammer, Hugo Lewi; Riegler, Michael; Halvorsen, Pål; de Lange, Thomas (Scientific Data;7, Article number: 283 (2020), Journal article; Peer reviewed, 2020-08-28)
      Artifcial intelligence is currently a hot topic in medicine. However, medical data is often sparse and hard to obtain due to legal restrictions and lack of medical personnel for the cumbersome and tedious process to manually ...
    • Impact of image resolution on deep learning performance in endoscopy image classification: An experimental study using a large dataset of endoscopic images 

      Thambawita, Vajira L B; Strumke, Inga; Hicks, Steven; Halvorsen, Pål; Parasa, Sravanthi; Riegler, Michael (Diagnostics;Volume 11 / Issue 12, Peer reviewed; Journal article, 2021-11-24)
      Recent trials have evaluated the efficacy of deep convolutional neural network (CNN)- based AI systems to improve lesion detection and characterization in endoscopy. Impressive results are achieved, but many medical studies ...
    • Kvasir-Capsule, a video capsule endoscopy dataset 

      Smedsrud, Pia H; Thambawita, Vajira L B; Hicks, Steven; Gjestang, Henrik; Olsen Nedrejord, Oda; Næss, Espen; Borgli, Hanna; Jha, Debesh; Berstad, Tor Jan; Eskeland, Sigrun Losada; Lux, Mathias; Espeland, Håvard; Petlund, Andreas; Dang Nguyen, Duc Tien; Garcia, Enrique; Johansen, Dag; Schmidt, Peter Thelin; Toth, Ervin; Hammer, Hugo Lewi; de Lange, Thomas; Riegler, Michael Alexander; Halvorsen, Pål (Scientific Data;8, Article number: 142 (2021), Peer reviewed; Journal article, 2021-05-27)
      Artificial intelligence (AI) is predicted to have profound effects on the future of video capsule endoscopy (VCE) technology. The potential lies in improving anomaly detection while reducing manual labour. Existing work ...
    • Machine Learning-Based Analysis of Sperm Videos and Participant Data for Male Fertility Prediction 

      Hicks, Steven; Andersen, Jorunn Marie; Witczak, Oliwia; Lasantha Bandara Thambawita, Vajira; Halvorsen, Pål; Hammer, Hugo Lewi; Haugen, Trine B.; Riegler, Michael Alexander (Scientific Reports;9, Article number: 16770 (2019), Journal article; Peer reviewed, 2019-10-24)
      Methods for automatic analysis of clinical data are usually targeted towards a specific modality and do not make use of all relevant data available. In the field of male human reproduction, clinical and biological data are ...
    • Meta-learning with implicit gradients in a few-shot setting for medical image segmentation 

      Khadka, Rabindra; Jha, Debesh; Riegler, Michael A.; Hicks, Steven; Thambawita, Vajira; Ali, Sharib; Halvorsen, Pål (Computers in Biology and Medicine;Volume 143, April 2022, 105227, Peer reviewed; Journal article, 2022-02-03)
      Widely used traditional supervised deep learning methods require a large number of training samples but often fail to generalize on unseen datasets. Therefore, a more general application of any trained model is quite limited ...
    • PMData: a sports logging dataset 

      Thambawita, Vajira; Hicks, Steven; Borgli, Hanna; Stensland, Håkon Kvale; Jha, Debesh; Svensen, Martin Kristoffer; Pettersen, Svein Arne; Johansen, Dag; Johansen, Håvard D.; Pettersen, Susann Dahl; Nordvang, Simon; Pedersen, Sigurd; Gjerdrum, Anders Tungeland; Grønli, Tor-Morten; Fredriksen, Per Morten; Eg, Ragnhild; Hansen, Kjeld S.; Fagernes, Siri; Claudi, Christine; Biørn-Hansen, Andreas; Dang Nguyen, Duc Tien; Kupka, Tomas; Hammer, Hugo Lewi; Jain, Ramesh; Riegler, Michael; Halvorsen, Pål (MM: International Multimedia Conference;MMSys '20: Proceedings of the 11th ACM Multimedia Systems Conference, Chapter; Conference object; Peer reviewed, 2020-05-27)
      In this paper, we present PMData: a dataset that combines traditional lifelogging data with sports-activity data. Our dataset enables the development of novel data analysis and machine-learning applications where, for ...
    • Prediction of cloud fractional cover using machine learning 

      Svennevik, Hanna; Riegler, Michael A.; Hicks, Steven; Storelvmo, Trude; Hammer, Hugo L. (Big Data and Cognitive Computing;Volume 5 / Issue 4, Peer reviewed; Journal article, 2021-11-03)
      Climate change is stated as one of the largest issues of our time, resulting in many unwanted effects on life on earth. Cloud fractional cover (CFC), the portion of the sky covered by clouds, might affect global warming ...
    • Real-Time Detection of Events in Soccer Videos using 3D Convolutional Neural Networks 

      Rognved, Olav; Hicks, Steven; Lasantha Bandara Thambawita, Vajira; Stensland, Håkon Kvale; Zouganeli, Evi; Johansen, Dag; Riegler, Michael A.; Halvorsen, Pål (IEEE International Symposium on Multimedia; 2020 IEEE International Symposium on Multimedia (ISM), Chapter; Peer reviewed, 2020-01-22)
      In this paper, we present an algorithm for automatically detecting events in soccer videos using 3D convolutional neural networks. The algorithm uses a sliding window approach to scan over a given video to detect events ...
    • Semantic Analysis of Soccer News for Automatic Game EventClassification 

      Nordskog, Aanund Jupskaas; Halvorsen, Pål; Hicks, Steven; Stensland, Haakon; Hammer, Hugo Lewi; Johansen, Dag; Riegler, Michael (International Workshop on Content-Based Multimedia Indexing, CBMI; 2019 International Conference on Content-Based Multimedia Indexing (CBMI), Chapter; Conference object; Peer reviewed, 2019-10-21)
      We are today overwhelmed with information, of which an important part is news. Sports news, in particular, has become very popular, where soccer makes up a big part of this coverage. For sports fans, it can be a time ...
    • Smittestopp analytics: Analysis of position data 

      Thambawita, Vajira L B; Hicks, Steven; Ewan, Jaouen; Halvorsen, Pål; Riegler, Michael (Simula SpringerBriefs on Computing;Volume 11, Chapter; Peer reviewed, 2022-06-18)
      Contact tracing applications generally rely on Bluetooth data. This type of data works well to determine whether a contact occurred (smartphones were close to each other) but cannot offer the contextual information GPS ...
    • Synthesizing a Talking Child Avatar to Train Interviewers Working with Maltreated Children 

      Salehi, Pegah; Hassan, Syed Zohaib; Lammerse, Myrthe; Shafiee Sabet, Saeed; Riiser, Ingvild; Røed, Ragnhild Klingenberg; Sinkerud Johnson, Miriam; Hicks, Steven; Thambawita, Vajira; Powell, Martine; Lamb, Michael E.; Baugerud, Gunn Astrid; Halvorsen, Pål; Riegler, Michael (Big Data and Cognitive Computing;Volume 6 / Issue 2, Peer reviewed; Journal article, 2022-06-01)
      When responding to allegations of child sexual, physical, and psychological abuse, Child Protection Service (CPS) workers and police personnel need to elicit detailed and accurate accounts of the abuse to assist in ...
    • Toadstool: a dataset for training emotional intelligent machines playing Super Mario Bros 

      Svoren, Henrik; Thambawita, Vajira; Halvorsen, Pål; Jakobsen, Petter; Garcia-Ceja, Enrique; Noori, Farzan Majeed; Hammer, Hugo Lewi; Lux, Mathias; Riegler, Michael; Hicks, Steven (MMSys: Multimedia Systems;MMSys '20: Proceedings of the 11th ACM Multimedia Systems Conference, Chapter; Conference object; Peer reviewed, 2020)
      Games are often defined as engines of experience, and they are heavily relying on emotions, they arouse in players. In this paper, we present a dataset called Toadstool as well as a reproducible methodology to extend ...
    • Using 3D Convolutional Neural Networks for Real-time Detection of Soccer Events 

      Rongved, Olav Andre Nergård; Hicks, Steven; Thambawita, Vajira L B; Stensland, Håkon Kvale; Zouganeli, Evi; Johansen, Dag; Riegler, Michael Alexander; Halvorsen, Pål (International Journal of Semantic Computing (IJSC);Volume 15, Issue 02, Peer reviewed; Journal article, 2021)
      Developing systems for the automatic detection of events in video is a task which has gained attention in many areas including sports. However, there are still a number of shortcomings with current systems, such as high ...
    • VISEM: A Multimodal Video Dataset of Human Spermatozoa 

      Haugen, Trine B.; Hicks, Steven; Andersen, Jorunn Marie; Witczak, Oliwia; Hammer, Hugo Lewi; Borgli, Rune Johan; Halvorsen, Pål; Riegler, Michael (ACM MMSys conference series;, Chapter; Peer reviewed, 2019)
      Real multimedia datasets that contain more than just images or text are rare. Even more so are open multimedia datasets in medicine. Often, clinically related datasets only consist of image or videos. In this paper, we ...