Example of GAN harmonization for Group 2.

<div><p>Purpose</p><p>Radiomics allows for the quantification of medical images and facilitates precision medicine. Many radiomic features derived from computed tomography (CT) are sensitive to variations across scanners, reconstruction settings, and acquisition protocols. In...

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Bibliographic Details
Main Author:	Shruti Atul Mali (21300851) (author)
Other Authors:	Nastaran Mohammadian Rad (18695473) (author), Henry C. Woodruff (6791684) (author), Adrien Depeursinge (8424390) (author), Vincent Andrearczyk (21300854) (author), Philippe Lambin (19883) (author)
Published:	2025
Subjects:	Biochemistry Medicine Cell Biology Biotechnology Infectious Diseases Space Science Biological Sciences not elsewhere classified generative adversarial networks facilitates precision medicine concordance correlation coefficient classification analysis revealed normal liver tissue variations across scanners gan increased reproducibility level harmonization approaches combination </ p level harmonization classification performance tissue classes tissue class xlink "> reconstruction settings phantom study medical images global reproducibility entire dataset discriminative power computed tomography comparative study benign cyst anthropomorphic phantom also harmonized acquisition protocols 93 texture 33 %. 24 %,
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Example of GAN harmonization for Group 2.

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