Machine learning-based radiomic analysis and growth visualization for ablation site recurrence diagnosis in follow-up CT

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: 1 Online-Ressource.

Language: Englisch

Bibliographic citation: Machine learning-based radiomic analysis and growth visualization for ablation site recurrence diagnosis in follow-up CT ; volume:49 ; number:4 ; day:30 ; month:1 ; year:2024 ; pages:1122-1131 ; date:4.2024
Abdominal radiology ; 49, Heft 4 (30.1.2024), 1122-1131, 4.2024

Creator: Yin, Yunchao
Haas, Robbert J. de
Alves, Natalia
Pennings, Jan Pieter
Ruiter, Simeon J. S.
Kwee, Thomas C.
Yakar, Derya

Contributor: SpringerLink (Online service)

DOI: 10.1007/s00261-023-04178-4

URN: urn:nbn:de:101:1-2405230709119.010036239065

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 14.08.2025, 10:51 AM CEST

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Yin, Yunchao
Haas, Robbert J. de
Alves, Natalia
Pennings, Jan Pieter
Ruiter, Simeon J. S.
Kwee, Thomas C.
Yakar, Derya
SpringerLink (Online service)

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Machine learning-based radiomic analysis and growth visualization for ablation site recurrence diagnosis in follow-up CT

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Other Objects (12)

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