Cargando…

CT based automatic clinical target volume delineation using a dense-fully connected convolution network for cervical Cancer radiation therapy

BACKGROUND: It is very important to accurately delineate the CTV on the patient’s three-dimensional CT image in the radiotherapy process. Limited to the scarcity of clinical samples and the difficulty of automatic delineation, the research of automatic delineation of cervical cancer CTV based on CT...

Descripción completa

Detalles Bibliográficos
Autores principales:	Ju, Zhongjian, Guo, Wen, Gu, Shanshan, Zhou, Jin, Yang, Wei, Cong, Xiaohu, Dai, Xiangkun, Quan, Hong, Liu, Jie, Qu, Baolin, Liu, Guocai
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2021
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7938586/ https://www.ncbi.nlm.nih.gov/pubmed/33685404 http://dx.doi.org/10.1186/s12885-020-07595-6

Ejemplares similares

Segmentation Algorithm of Magnetic Resonance Imaging Glioma under Fully Convolutional Densely Connected Convolutional Networks
por: Dong, Jie, et al.
Publicado: (2022)

Retracted: Segmentation Algorithm of Magnetic Resonance Imaging Glioma under Fully Convolutional Densely Connected Convolutional Networks
por: International, Stem Cells
Publicado: (2023)

Automatic Detection of Cone Photoreceptors With Fully Convolutional Networks
por: Hamwood, Jared, et al.
Publicado: (2019)

Cell‐free RNA and fully convolutional dense network‐based early preeclampsia prediction
por: Zhao, Zhuo, et al.
Publicado: (2023)

HADCNet: Automatic segmentation of COVID-19 infection based on a hybrid attention dense connected network with dilated convolution
por: Chen, Ying, et al.
Publicado: (2022)

N-Net: A novel dense fully convolutional neural network for thyroid nodule segmentation
por: Nie, Xingqing, et al.
Publicado: (2022)

IrisDenseNet: Robust Iris Segmentation Using Densely Connected Fully Convolutional Networks in the Images by Visible Light and Near-Infrared Light Camera Sensors
por: Arsalan, Muhammad, et al.
Publicado: (2018)

Fully Convolutional DenseNet with Multiscale Context for Automated Breast Tumor Segmentation
por: Hai, Jinjin, et al.
Publicado: (2019)

Recovery of Ionospheric Signals Using Fully Convolutional DenseNet and Its Challenges
por: Mendoza, Merlin M., et al.
Publicado: (2021)

Fully automatic wound segmentation with deep convolutional neural networks
por: Wang, Chuanbo, et al.
Publicado: (2020)

Verte-Box: A Novel Convolutional Neural Network for Fully Automatic Segmentation of Vertebrae in CT Image
por: Li, Bing, et al.
Publicado: (2022)

Corrigendum: N-Net: A novel dense fully convolutional neural network for thyroid nodule segmentation
por: Nie, Xingqing, et al.
Publicado: (2022)

Automatic Search Dense Connection Module for Super-Resolution
por: Zang, Huaijuan, et al.
Publicado: (2022)

Automatic delineation of functional lung volumes with (68)Ga-ventilation/perfusion PET/CT
por: Le Roux, Pierre-Yves, et al.
Publicado: (2017)

Automatic liver tumor segmentation in CT with fully convolutional neural networks and object-based postprocessing
por: Chlebus, Grzegorz, et al.
Publicado: (2018)

Convolutional neural networks for PET functional volume fully automatic segmentation: development and validation in a multi-center setting
por: Iantsen, Andrei, et al.
Publicado: (2021)

Gait Recognition Method of Underground Coal Mine Personnel Based on Densely Connected Convolution Network and Stacked Convolutional Autoencoder
por: Liu, Xiaoyang, et al.
Publicado: (2020)

A convolutional neural network with self-attention for fully automated metabolic tumor volume delineation of head and neck cancer in [Formula: see text] F]FDG PET/CT
por: Nikulin, Pavel, et al.
Publicado: (2023)

A-DenseUNet: Adaptive Densely Connected UNet for Polyp Segmentation in Colonoscopy Images with Atrous Convolution
por: Safarov, Sirojbek, et al.
Publicado: (2021)

Densely connected convolutional networks-based COVID-19 screening model
por: Singh, Dilbag, et al.
Publicado: (2021)

Attention-Guided Network with Densely Connected Convolution for Skin Lesion Segmentation
por: Tao, Shengxin, et al.
Publicado: (2021)

DCNet: Densely Connected Deep Convolutional Encoder–Decoder Network for Nasopharyngeal Carcinoma Segmentation
por: Li, Yang, et al.
Publicado: (2021)

Automatic labeling of molecular biomarkers of immunohistochemistry images using fully convolutional networks
por: Sheikhzadeh, Fahime, et al.
Publicado: (2018)

Skin Lesion Classification Using Densely Connected Convolutional Networks with Attention Residual Learning
por: Wu, Jing, et al.
Publicado: (2020)

Liver tumor segmentation in CT volumes using an adversarial densely connected network
por: Chen, Lei, et al.
Publicado: (2019)

A Multi-Scale Densely Connected Convolutional Neural Network for Automated Thyroid Nodule Classification
por: Wang, Luoyan, et al.
Publicado: (2022)

Delineation of agricultural fields in smallholder farms from satellite images using fully convolutional networks and combinatorial grouping
por: Persello, C., et al.
Publicado: (2019)

A deep convolutional neural network-based automatic delineation strategy for multiple brain metastases stereotactic radiosurgery
por: Liu, Yan, et al.
Publicado: (2017)

Fully Automatic Whole-Volume Tumor Segmentation in Cervical Cancer
por: Hodneland, Erlend, et al.
Publicado: (2022)

Crop pest image classification based on improved densely connected convolutional network
por: Peng, Hongxing, et al.
Publicado: (2023)

Automatic Segmentation for Favourable Delineation of Ten Wrist Bones on Wrist Radiographs Using Convolutional Neural Network
por: Kang, Bo-kyeong, et al.
Publicado: (2022)

Fully automatic acute ischemic lesion segmentation in DWI using convolutional neural networks
por: Chen, Liang, et al.
Publicado: (2017)

Fully Automatic Atrial Fibrosis Assessment Using a Multilabel Convolutional Neural Network
por: Razeghi, Orod, et al.
Publicado: (2020)

Automatic seizure detection based on imaged-EEG signals through fully convolutional networks
por: Gómez, Catalina, 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)

Mine MIMO Depth Receiver: An Intelligent Receiving Model Based on Densely Connected Convolutional Networks
por: Wang, Mingbo, et al.
Publicado: (2021)

Joint optic disc and cup segmentation based on densely connected depthwise separable convolution deep network
por: Liu, Bingyan, et al.
Publicado: (2021)

Impact of the EARL harmonization program on automatic delineation of metabolic active tumour volumes (MATVs)
por: Lasnon, Charline, et al.
Publicado: (2017)

Citrus Pests and Diseases Recognition Model Using Weakly Dense Connected Convolution Network
por: Xing, Shuli, et al.
Publicado: (2019)

Fully Automated Delineation of Gross Tumor Volume for Head and Neck Cancer on PET-CT Using Deep Learning: A Dual-Center Study
por: Huang, Bin, et al.
Publicado: (2018)

Cannot write session to /tmp/vufind_sessions/sess_dl2m5cb8r792t9b8soatl7o6g1