Training-free image style alignment for domain shift on handheld ultrasound devices

Handheld ultrasound devices face usage limitations due to user inexperience and cannot benefit from supervised deep learning without extensive expert annotations. Moreover, the models trained on standard ultrasound device data are constrained by training data distribution and perform poorly when dir...

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Veröffentlicht in:	IEEE transactions on medical imaging 2025, p.1-1
Hauptverfasser:	Zeng, Hongye, Zou, Ke, Chen, Zhihao, Gao, Yuchong, Chen, Hongbo, Zhang, Haibin, Zhou, Kang, Wang, Meng, Jiang, Chang, Goh, Rick Siow Mong, Liu, Yong, Zhu, Chengcheng, Zheng, Rui, Fu, Huazhu
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation models Annotations Computational modeling Data models Diffusion models handheld ultrasound device Measurement uncertainty Predictive models test-time domain adaptation Training-free alignment Ultrasonic imaging ultrasound images Uncertainty
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