Clinical application of mask region-based convolutional neural network for the automatic detection and segmentation of abnormal liver density based on hepatocellular carcinoma computed tomography datasets.
The aim of the study was to use a previously proposed mask region-based convolutional neural network (Mask R-CNN) for automatic abnormal liver density detection and segmentation based on hepatocellular carcinoma (HCC) computed tomography (CT) datasets from a radiological perspective. Training and te...
Guardado en:
Autores principales: | Ching-Juei Yang, Chien-Kuo Wang, Yu-Hua Dean Fang, Jing-Yao Wang, Fong-Chin Su, Hong-Ming Tsai, Yih-Jyh Lin, Hung-Wen Tsai, Lee-Ren Yeh |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Public Library of Science (PLoS)
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/dfaeedd751594b4385b21073abf16088 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Automatic recognition of murmurs of ventricular septal defect using convolutional recurrent neural networks with temporal attentive pooling
por: Jou-Kou Wang, et al.
Publicado: (2020) -
Fully automatic wound segmentation with deep convolutional neural networks
por: Chuanbo Wang, et al.
Publicado: (2020) -
An Automatic Light Stress Grading Architecture Based on Feature Optimization and Convolutional Neural Network
por: Xia Hao, et al.
Publicado: (2021) -
Circular convolution-based feature extraction algorithm for classification of high-dimensional datasets
por: Tajanpure Rupali, et al.
Publicado: (2021) -
Automatic Interferogram Selection for SBAS-InSAR Based on Deep Convolutional Neural Networks
por: Yufang He, et al.
Publicado: (2021)