CT2US: Cross-modal transfer learning for kidney segmentation in ultrasound images with synthesized data

•Ultrasound images with annotations are scarce, hampering the application of deep learning methods.•A cross-modal transfer learning strategy is proposed by leveraging annotated data in CT modality.•CycleGAN is adopted to synthesize US images from CT images and construct a transition dataset.•Mainstr...

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Vydáno v:	Ultrasonics Ročník 122; s. 106706
Hlavní autoři:	Song, Yuxin, Zheng, Jing, Lei, Long, Ni, Zhipeng, Zhao, Baoliang, Hu, Ying
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Netherlands Elsevier B.V 01.05.2022
Témata:	Cross modality Datasets as Topic Deep Learning Humans Image Processing, Computer-Assisted - methods Kidney - diagnostic imaging Kidney segmentation Tomography, X-Ray Computed Transfer learning Ultrasonography Ultrasound imaging Cross modality Transfer learning Ultrasound imaging Kidney segmentation
ISSN:	0041-624X, 1874-9968, 1874-9968
On-line přístup:	Získat plný text
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