Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Michael Osadebey"'
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 23, Iss 1, Pp 1-12 (2023)
Abstract Background Saliency-based algorithms are able to explain the relationship between input image pixels and deep-learning model predictions. However, it may be difficult to assess the clinical value of the most important image features and the
Externí odkaz:
https://doaj.org/article/87ef5160b36a40ea958482c093e27f95
Autor:
Michael Osadebey, Hilde K. Andersen, Dag Waaler, Kristian Fossaa, Anne C. T. Martinsen, Marius Pedersen
Publikováno v:
BMC Medical Imaging, Vol 21, Iss 1, Pp 1-19 (2021)
Abstract Background Lung region segmentation is an important stage of automated image-based approaches for the diagnosis of respiratory diseases. Manual methods executed by experts are considered the gold standard, but it is time consuming and the ac
Externí odkaz:
https://doaj.org/article/58bfb0e574104d8d94c8c18a2b15ad22
Publikováno v:
IEEE Journal of Translational Engineering in Health and Medicine, Vol 6, Pp 1-15 (2018)
Magnetic resonance imaging (MRI) system images are important components in the development of drugs because it can reveal the underlying pathology in diseases. Unfortunately, the processes of image acquisition, storage, transmission, processing, and
Externí odkaz:
https://doaj.org/article/970fa55a4a8f44c9876b69765a515702
Publikováno v:
Journal of Imaging, Vol 5, Iss 1, p 20 (2019)
Noise-based quality evaluation of MRI images is highly desired in noise-dominant environments. Current noise-based MRI quality evaluation methods have drawbacks which limit their effective performance. Traditional full-reference methods such as SNR a
Externí odkaz:
https://doaj.org/article/35655a6d2b6349719d22a13fa2a4bea3
Publikováno v:
Expert systems
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::61af67b8bcfc3d27284ee81d4b526ba3
https://hdl.handle.net/11250/3047384
https://hdl.handle.net/11250/3047384
Autor:
Dag Waaler, Hilde Kjernlie Andersen, Marius Pedersen, Michael Osadebey, Kristian Fossaa, Anne Catrine Trægde Martinsen
Publikováno v:
BMC Medical Imaging
BMC Medical Imaging, Vol 21, Iss 1, Pp 1-19 (2021)
BMC Medical Imaging, Vol 21, Iss 1, Pp 1-19 (2021)
Background Lung region segmentation is an important stage of automated image-based approaches for the diagnosis of respiratory diseases. Manual methods executed by experts are considered the gold standard, but it is time consuming and the accuracy is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::73791dd0b1b6dea80d5686bf11ee9f27
https://hdl.handle.net/11250/2785860
https://hdl.handle.net/11250/2785860
Publikováno v:
Unsupervised and Semi-Supervised Learning ISBN: 9783030238759
Data mining is an extensive area of research involving pattern discovery and feature extraction which is applied in various critical domains. In clinical aspect, data mining has emerged to assist the clinicians in early detection, diagnosis, and prev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b5148b23a503c56f652164d626a6456d
https://doi.org/10.1007/978-3-030-23876-6_11
https://doi.org/10.1007/978-3-030-23876-6_11
Publikováno v:
INDIN
IEEE Conference on Industrial Informatics
IEEE Conference on Industrial Informatics
Presence of clutters and occluding objects within agricultural farm environments challenges accurate segmentation of plant leaves, a prerequisite for an effective machine-vision-based automation of agricultural tasks. In this paper, we propose a plan
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c90d9c7470c38768dd74876db0b5d780
https://hdl.handle.net/11250/2647746
https://hdl.handle.net/11250/2647746
Publikováno v:
Journal of Imaging
Journal of Imaging, Vol 5, Iss 1, p 20 (2019)
Volume 5
Issue 1
Journal of Imaging, Vol 5, Iss 1, p 20 (2019)
Volume 5
Issue 1
Noise-based quality evaluation of MRI images is highly desired in noise-dominant environments. Current noise-based MRI quality evaluation methods have drawbacks which limit their effective performance. Traditional full-reference methods such as SNR a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ace3a7376d8c8e62a80e462fe070ea15
https://pubmed.ncbi.nlm.nih.gov/34465703
https://pubmed.ncbi.nlm.nih.gov/34465703
Publikováno v:
BioMedical Engineering
Biomedical engineering
BioMedical Engineering OnLine, Vol 17, Iss 1, Pp 1-22 (2018)
Biomedical engineering
BioMedical Engineering OnLine, Vol 17, Iss 1, Pp 1-22 (2018)
Background: Rician noise, bias felds and blur are the common distortions that degrade MRI images during acquisition. Blur is unique in comparison to Rician noise and bias felds because it can be introduced into an image beyond the acquisition stage s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::58752a98180661b45d2be8385a236a49
http://hdl.handle.net/11250/2557779
http://hdl.handle.net/11250/2557779