Comparison of diagnostic accuracy of radiomics parameter maps and standard reconstruction for the detection of liver lesions in computed tomography

The application of firstorder RootMeanSquared feature maps may help visualize faintly demarcated liver lesions by increasing visual contrast. However, reading of SCTR remains necessary for diagnostic confidence.

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Publication Details

Journal
Frontiers in Oncology
Published
2024-10-07
DOI
https://doi.org/10.3389/fonc.2024.1444115
Citations
4
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
1.62
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article

Comparison of diagnostic accuracy of radiomics parameter maps and standard reconstruction for the detection of liver lesions in computed tomography

Nils Rathmann, Alexander Hertel, Dominik Nörenberg, Hishan Tharmaseelan et al.
4 citations
Frontiers in Oncology
Radiomics and Machine Learning in Medical Imaging
1.62
article

Comparison of diagnostic accuracy of radiomics parameter maps and standard reconstruction for the detection of liver lesions in computed tomography

Nils Rathmann, Alexander Hertel, Dominik Nörenberg, Hishan Tharmaseelan, Fabian Tollens, Stefan O. Schoenberg, Matthias F. Froelich, Mustafa Kuru
article en
4 citations

Abstract

The application of firstorder RootMeanSquared feature maps may help visualize faintly demarcated liver lesions by increasing visual contrast. However, reading of SCTR remains necessary for diagnostic confidence.

Frontiers in OncologyVol. 14
Heidelberg University (DE), University Hospital Heidelberg (DE), University Medical Centre Mannheim (DE)
Good health and well-being
Openalex Percentile: Top 16%
Radiomics and Machine Learning in Medical Imaging
1.62
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