A Comparative Literature Review of Machine Learning and Image Processing Techniques Used for Scaling and Grading of Wood Logs

Autor: Yohann Jacob Sandvik, Cecilia Marie Futsæther, Kristian Hovde Liland, Oliver Tomic

Publikováno v: Forests, Vol 15, Iss 7, p 1243 (2024)

This literature review assesses the efficacy of image-processing techniques and machine-learning models in computer vision for wood log grading and scaling. Four searches were conducted in four scientific databases, yielding a total of 1288 results,

Externí odkaz: https://doaj.org/article/53e566b0cff94bd09de71687580e5b0b

Automatic gross tumor segmentation of canine head and neck cancer using deep learning and cross-species transfer learning

Autor: Aurora Rosvoll Groendahl, Bao Ngoc Huynh, Oliver Tomic, Åste Søvik, Einar Dale, Eirik Malinen, Hege Kippenes Skogmo, Cecilia Marie Futsaether

Publikováno v: Frontiers in Veterinary Science, Vol 10 (2023)

BackgroundRadiotherapy (RT) is increasingly being used on dogs with spontaneous head and neck cancer (HNC), which account for a large percentage of veterinary patients treated with RT. Accurate definition of the gross tumor volume (GTV) is a vital pa

Externí odkaz: https://doaj.org/article/ed5a8a1442144238a84f82b51d2a98de

30-Day Survival Probabilities as a Quality Indicator for Norwegian Hospitals: Data Management and Analysis.

Autor: Sahar Hassani, Anja Schou Lindman, Doris Tove Kristoffersen, Oliver Tomic, Jon Helgeland

Publikováno v: PLoS ONE, Vol 10, Iss 9, p e0136547 (2015)

The Norwegian Knowledge Centre for the Health Services (NOKC) reports 30-day survival as a quality indicator for Norwegian hospitals. The indicators have been published annually since 2011 on the website of the Norwegian Directorate of Health (www.he

Externí odkaz: https://doaj.org/article/1e644bda3e0449c38b5a04046f33c122

Deep learning-based automatic delineation of anal cancer gross tumour volume: a multimodality comparison of CT, PET and MRI

Autor: Bettina Hanekamp, Cecilia M. Futsaether, Christine Kiran Kaushal, Oliver Tomic, Aurora Rosvoll Groendahl, Eivor Hernes, Bao Ngoc Huynh, Yngve Mardal Moe, Eirik Malinen, Marianne Grønlie Guren, Christine Undseth, Espen Rusten

Publikováno v: Acta Oncologica. 61:89-96

Background Accurate target volume delineation is a prerequisite for high-precision radiotherapy. However, manual delineation is resource-demanding and prone to interobserver variation. An automatic delineation approach could potentially save time and

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::590d0390c2398484fd442867eda26bc7
https://doi.org/10.1080/0284186x.2021.1994645

PET Normalizations to Improve Deep Learning Auto-Segmentation of Head and Neck Tumors in 3D PET/CT

Autor: Jintao Ren, Bao-Ngoc Huynh, Aurora Rosvoll Groendahl, Oliver Tomic, Cecilia Marie Futsaether, Stine Sofia Korreman

Publikováno v: Ren, J, Huynh, B-N, Groendahl, A R, Tomic, O, Futsaether, C M & Korreman, S S 2022, PET Normalizations to Improve Deep Learning Auto-Segmentation of Head and Neck Tumors in 3D PET/CT . in 3D Head and Neck Tumor Segmentation in PET/CT Challenge : Second Challenge, HECKTOR 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings . Springer, Cham, Lecture Notes in Computer Science, vol. 13209, pp. 83-91 . https://doi.org/10.1007/978-3-030-98253-9_7
Lecture Notes in Computer Science ISBN: 9783030982522

Auto-segmentation of head and neck cancer (HNC) primary gross tumor volume (GTVt) is a necessary but challenging process for radiotherapy treatment planning and radiomics studies. The HEad and neCK TumOR Segmentation Challenge (HECKTOR) 2021 comprise

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7a140ce2e5dadb098dd7b4d133aae4f9
https://pure.au.dk/portal/da/publications/pet-normalizations-to-improve-deep-learning-autosegmentation-of-head-and-neck-tumors-in-3d-petct(e5af1a6e-aab3-40b8-9f68-35df9c0eacd4).html