Joint segmentation and classification of hepatic lesions in ultrasound images using deep learning

OBJECTIVES: To develop a convolutional neural network system to jointly segment and classify a hepatic lesion selected by user clicks in ultrasound images. METHODS: In total, 4309 anonymized ultrasound images of 3873 patients with hepatic cyst (n = 1214), hemangioma (n = 1220), metastasis (n = 1001)...

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Detalles Bibliográficos
Autores principales: Ryu, Hwaseong, Shin, Seung Yeon, Lee, Jae Young, Lee, Kyoung Mu, Kang, Hyo-jin, Yi, Jonghyon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Imaging Informatics and Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8523410/
https://www.ncbi.nlm.nih.gov/pubmed/33881566
http://dx.doi.org/10.1007/s00330-021-07850-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8523410/
https://www.ncbi.nlm.nih.gov/pubmed/33881566
http://dx.doi.org/10.1007/s00330-021-07850-9

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