Blar i Sentraladministrasjonen på forfatter "de Lange, Thomas"

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    • Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge 

      Ali, Sharib; Ghatwary, Noha; Jha, Debesh; Isik-Polat, Ece; Polat, Gorkem; Yang, Cheng; Li, Wuyang; Galdran, Adrian; Ballester, Miguel Angel Gonzalez; Thambawita, Vajira L B; Hicks, Steven; Poudel, Sahadev; Lee, Sang-Woong; Jin, Ziyi; Gan, Tianyuan; Yu, Chenghui; Yan, JiangPeng; Yeo, Doyeob; Lee, Hyunseok Lee; Tomar, Nikhil Kumar; Haitham, Mahmood; Ahmed, Amr; Riegler, Michael Alexander; Daul, Christian; Halvorsen, Pål; Rittscher, Jens; Salem, Osama E.; Lamarque, Dominique; Cannizzaro, Renato; Realdon, Stefano; de Lange, Thomas; East, James E (Peer reviewed; Journal article, 2024)
      Polyps are well‑known cancer precursors identified by colonoscopy. However, variability in their size, appearance, and location makes the detection of polyps challenging. Moreover, colonoscopy surveillance and removal ...

    • 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 ...

    • The CRCbiome study: a large prospective cohort study examining the role of lifestyle and the gut microbiome in colorectal cancer screening participants 

      Kværner, Ane Sørlie; Birkeland, Einar Elvbakken; Bucher-Johannessen, Cecilie; Vinberg, Elina; Nordby, Jan Inge; Kangas, Harri; Bemanian, Vahid; Ellonen, Pekka; Botteri, Edoardo; Natvig, Erik; Rognes, Torbjørn; Hovig, Eivind; Lyle, Robert; Ambur, Ole Herman; de Vos, Willem M.; Bultman, Scott J; Hjartåker, Anette; Landberg, Rikard; Song, Mingyang; Blix, Hege Salvesen; Ursin, Giske; Randel, Kristin Ranheim; de Lange, Thomas; Hoff, Geir; Holme, Øyvind; Berstad, Paula; Rounge, Trine Ballestad (BMC Cancer;21, Article number: 930 (2021), Peer reviewed; Journal article, 2021-08-18)
      Background: Colorectal cancer (CRC) screening reduces CRC incidence and mortality. However, current screening methods are either hampered by invasiveness or suboptimal performance, limiting their effectiveness as primary ...

    • 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 ...

    • Man vs. AI: An in silico study of polyp detection performance 

      Smedsrud, Pia Helen; Espeland, Håvard; Berstad, Tor Jan; Petlund, Andreas; de Lange, Thomas; Riegler, Michael; Halvorsen, Pål (Annual IEEE Symposium on Computer-Based Medical Systems;, Chapter; Peer reviewed; Conference object; Journal article, 2023)
      AI-based colon polyp detection systems have received much attention, and several products and prototypes report good results. In silico verification is a crucial step when developing such systems, but very few compare human ...

    • A multi-centre polyp detection and segmentation dataset for generalisability assessment 

      Ali, Sharib; Jha, Debesh; Ghatwary, Noha; Realdon, Stefano; Cannizzaro, Renato; Salem, Osama E.; Lamarque, Dominique; Daul, Christian; Riegler, Michael Alexander; Ånonsen, Kim Vidar; Petlund, Andreas; Halvorsen, Pål; Rittscher, Jens; de Lange, Thomas; East, James E (Peer reviewed; Journal article, 2023)

    • PolypConnect: Image inpainting for generating realistic gastrointestinal tract images with polyps 

      Fagereng, Jan Andre; Thambawita, Vajira L B; Storås, Andrea; Parasa, Sravanthi; de Lange, Thomas; Halvorsen, Pål; Riegler, Michael (Annual IEEE Symposium on Computer-Based Medical Systems;2022 IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS), Conference object, 2022)
      Early identification of a polyp in the lower gastrointestinal (GI) tract can lead to prevention of life-threatening colorectal cancer. Developing computer-aided diagnosis (CAD) systems to detect polyps can improve detection ...

    • SinGAN-Seg: Synthetic training data generation for medical image segmentation 

      Thambawita, Vajira L B; Salehi, Pegah; Sheshkal, Sajad Amouei; Hicks, Steven; Hammer, Hugo Lewi; Parasa, Sravanthi; de Lange, Thomas; Halvorsen, Pål; Riegler, Michael (PLOS ONE;17(5): e0267976, Peer reviewed; Journal article, 2022-05-02)
      Analyzing medical data to find abnormalities is a time-consuming and costly task, particularly for rare abnormalities, requiring tremendous efforts from medical experts. Therefore, artificial intelligence has become a ...