Výsledky vyhledávání - "Tobias, Lasser"

Akademický článek

Improving image quality of sparse-view lung tumor CT images with U-Net

Autor: Annika Ries, Tina Dorosti, Johannes Thalhammer, Daniel Sasse, Andreas Sauter, Felix Meurer, Ashley Benne, Tobias Lasser, Franz Pfeiffer, Florian Schaff, Daniela Pfeiffer

Publikováno v: European Radiology Experimental, Vol 8, Iss 1, Pp 1-11 (2024)

Abstract Background We aimed to improve the image quality (IQ) of sparse-view computed tomography (CT) images using a U-Net for lung metastasis detection and determine the best tradeoff between number of views, IQ, and diagnostic confidence. Methods

Externí odkaz: https://doaj.org/article/bd21aaaaed814299bd1721f3ec8cdcb0

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Akademický článek

Revealing clinically relevant specific IgE sensitization patterns in Hymenoptera venom allergy with dimension reduction and clusteringKey messagesCapsule summary

Autor: Robert Kaczmarczyk, MD, Tobias Lasser, PhD, Tilo Biedermann, MD, Johannes Ring, MD, Alexander Zink, MD

Publikováno v: World Allergy Organization Journal, Vol 16, Iss 10, Pp 100820- (2023)

Background: Immunoglobulin E (IgE) blood tests are used to detect sensitizations and potential allergies. Recent studies suggest that specific IgE sensitization patterns due to molecular interactions affect an individual's risk of developing allergic

Externí odkaz: https://doaj.org/article/daa4c221062b4383ac8e6da301952ad3

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Akademický článek

WindowNet: Learnable Windows for Chest X-ray Classification

Autor: Alessandro Wollek, Sardi Hyska, Bastian Sabel, Michael Ingrisch, Tobias Lasser

Publikováno v: Journal of Imaging, Vol 9, Iss 12, p 270 (2023)

Public chest X-ray (CXR) data sets are commonly compressed to a lower bit depth to reduce their size, potentially hiding subtle diagnostic features. In contrast, radiologists apply a windowing operation to the uncompressed image to enhance such subtl

Externí odkaz: https://doaj.org/article/c0ea9511f4f04042824141f5e31878cc

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Outlier detection in dermatology: Performance of different convolutional neural networks for binary classification of inflammatory skin diseases

Autor: Maximilian C. Schielein, Joshua Christl, Sebastian Sitaru, Anna Caroline Pilz, Robert Kaczmarczyk, Tilo Biedermann, Tobias Lasser, Alexander Zink

Publikováno v: Journal of the European Academy of Dermatology and Venereology. 37:1071-1079

Artificial intelligence (AI) and convolutional neural networks (CNNs) represent rising trends in modern medicine. However, comprehensive data on the performance of AI practices in clinical dermatologic images are non-existent. Furthermore, the role o

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::32bd4ee82f7861f24fe7718b5546860b
https://doi.org/10.1111/jdv.18853

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Advanced Phase-Retrieval for Stepping-Free X-Ray Dark-Field Computed Tomography

Autor: Jakob Haeusele, Clemens Schmid, Manuel Viermetz, Nikolai Gustschin, Tobias Lasser, Thomas Koehler, Franz Pfeiffer

Grating-based phase- and dark-field-contrast X-ray imaging is a novel technology that aims to extend conventional attenuation-based X-ray imaging by unlocking two additional contrast modalities. The so called phase-contrast and dark-field channels pr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a156044e94330ade1dc120414c5725de
https://doi.org/10.36227/techrxiv.21803598

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