Collimation border with U-Net segmentation on chest radiographs compared to radiologists

Autor: A.E. Pedersen, M.W. Kusk, G.H. Knudsen, C.A.G.R. Busk, S. Lysdahlgaard

Publikováno v: Radiography. 29:647-652

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::445fbe2279b6a846dac060e2d5039460
https://doi.org/10.1016/j.radi.2023.04.016

The effect of Gaussian noise on pneumonia detection on chest radiographs, using convolutional neural networks

Autor: M.W. Kusk, S. Lysdahlgaard

Publikováno v: Radiography. 29:38-43

Chest X-rays (CXR) with under-exposure increase image noise and this may affect convolutional neural network (CNN) performance. This study aimed to train and validate CNNs for classifying pneumonia on CXR as normal or pneumonia acquired at different

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::919a0cf926abe055efe6cbe7bee47dc2
https://doi.org/10.1016/j.radi.2022.09.011

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Image quality of bedside chest radiographs in intensive care beds with integrated detector tray:A phantom study

Autor: S. Enevoldsen, M.W. Kusk

Publikováno v: Enevoldsen, S & Kusk, M W 2021, ' Image quality of bedside chest radiographs in intensive care beds with integrated detector tray : A phantom study ', Radiography, vol. 27, no. 2, pp. 453-458 . https://doi.org/10.1016/j.radi.2020.10.012

Introduction Vendors offer intensive care beds with integrated detector trays for bedside radiography, promoting better ergonomics and patient comfort. However, no documentation of the effects on diagnostic image quality has been located. This study

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ee14a2fcb65f7200332ea4aaf4304b51
https://portal.findresearcher.sdu.dk/da/publications/d665327a-6f72-4a5d-91ab-ac5f3c934746