Cargando…
A Three-Dimensional Deep Convolutional Neural Network for Automatic Segmentation and Diameter Measurement of Type B Aortic Dissection
OBJECTIVE: To provide an automatic method for segmentation and diameter measurement of type B aortic dissection (TBAD). MATERIALS AND METHODS: Aortic computed tomography angiographic images from 139 patients with TBAD were consecutively collected. We implemented a deep learning method based on a thr...
Autores principales: | Yu, Yitong, Gao, Yang, Wei, Jianyong, Liao, Fangzhou, Xiao, Qianjiang, Zhang, Jie, Yin, Weihua, Lu, Bin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Korean Society of Radiology
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7817629/ https://www.ncbi.nlm.nih.gov/pubmed/33236538 http://dx.doi.org/10.3348/kjr.2020.0313 |
Ejemplares similares
-
Automatic localization and segmentation of focal cortical dysplasia in FLAIR‐negative patients using a convolutional neural network
por: Feng, Cuixia, et al.
Publicado: (2020) -
Automatic detection of contouring errors using convolutional neural networks
por: Rhee, Dong Joo, et al.
Publicado: (2019) -
Fully automatic wound segmentation with deep convolutional neural networks
por: Wang, Chuanbo, et al.
Publicado: (2020) -
Automatic diagnosis of macular diseases from OCT volume based on its two-dimensional feature map and convolutional neural network with attention mechanism
por: Sun, Yankui, et al.
Publicado: (2020) -
A benchmark study of convolutional neural networks in fully automatic segmentation of aortic root
por: Yang, Tingting, et al.
Publicado: (2023)