Multimodal medical image‐to‐image translation via variational autoencoder latent space mapping

Background Medical image translation has become an essential tool in modern radiotherapy, providing complementary information for target delineation and dose calculation. However, current approaches are constrained by their modality‐specific nature, requiring separate model training for each pair of...

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Veröffentlicht in:	Medical physics (Lancaster) Jg. 52; H. 7; S. e17912 - n/a
Hauptverfasser:	Liang, Zhiwen, Cheng, Mengjie, Ma, Jinhui, Hu, Ying, Li, Song, Tian, Xin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States 01.07.2025
Schlagworte:	adaptive radiotherapy Autoencoder bidirectional transformer Cone-Beam Computed Tomography deep learning Head and Neck Neoplasms - diagnostic imaging Humans Image Processing, Computer-Assisted - methods latent space mapping Magnetic Resonance Imaging Multimodal Imaging - methods multimodality image translation deep learning multimodality image translation latent space mapping bidirectional transformer adaptive radiotherapy
ISSN:	0094-2405, 2473-4209, 2473-4209
Online-Zugang:	Volltext
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