Výsledky vyhledávání - "Ronghui Tian"

Akademický článek

Deep learning radiomics based on multimodal imaging for distinguishing benign and malignant breast tumours

Autor: Guoxiu Lu, Ronghui Tian, Wei Yang, Ruibo Liu, Dongmei Liu, Zijie Xiang, Guoxu Zhang

Publikováno v: Frontiers in Medicine, Vol 11 (2024)

ObjectivesThis study aimed to develop a deep learning radiomic model using multimodal imaging to differentiate benign and malignant breast tumours.MethodsMultimodality imaging data, including ultrasonography (US), mammography (MG), and magnetic reson

Externí odkaz: https://doaj.org/article/d85bff7a5521400e88624582aa53730a

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Akademický článek

Fus2Net: a novel Convolutional Neural Network for classification of benign and malignant breast tumor in ultrasound images

Autor: He Ma, Ronghui Tian, Hong Li, Hang Sun, Guoxiu Lu, Ruibo Liu, Zhiguo Wang

Publikováno v: BioMedical Engineering OnLine, Vol 20, Iss 1, Pp 1-15 (2021)

Abstract Background The rapid development of artificial intelligence technology has improved the capability of automatic breast cancer diagnosis, compared to traditional machine learning methods. Convolutional Neural Network (CNN) can automatically s

Externí odkaz: https://doaj.org/article/3547486f0dda4b46a3ec8400cf4e253f

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An effective convolutional neural network for classification of benign and malignant breast and thyroid tumors from ultrasound images

Autor: Ronghui Tian, Miao Yu, Lingmin Liao, Chunquan Zhang, Jiali Zhao, Liang Sang, Wei Qian, Zhiguo Wang, Long Huang, He Ma

Publikováno v: Physical and Engineering Sciences in Medicine.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::120a00facc6178130a03f15d512be450
https://doi.org/10.1007/s13246-023-01262-3

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Fus2Net: a novel Convolutional Neural Network for classification of benign and malignant breast tumor in ultrasound images

Autor: Hang Sun, He Ma, Guoxiu Lu, Ruibo Liu, Ronghui Tian, Hong Li, Zhiguo Wang

Publikováno v: BioMedical Engineering OnLine, Vol 20, Iss 1, Pp 1-15 (2021)
BioMedical Engineering

BackgroundThe rapid development of artificial intelligence technology has improved the capability of automatic breast cancer diagnosis, compared to traditional machine learning methods. Convolutional Neural Network (CNN) can automatically select high

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2a1bb639d7a35b90e035c1b5d463d4c0
https://doaj.org/article/3547486f0dda4b46a3ec8400cf4e253f

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