About: Evaluation of deep learning methods for parotid gland segmentation from CT images

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scientific article published on 01 October 2018

Attributes	Values
rdf:type	Item
description	wetenschappelijk artikel (nl) наукова стаття, опублікована в січні 2019 (uk) im Oktober 2018 veröffentlichter wissenschaftlicher Artikel (de) scientific article published on 01 October 2018 (en) artículu científicu espublizáu n'ochobre de 2018 (ast)
publication date	wds:Q57022926-72FBBBF5-5E3B-4FC2-8600-CA4F139135E5
publication date	2018-10-01 00:00:00Z (xsd:dateTime)
language of work or name	wds:Q57022926-8BFE85C4-1521-4C04-961E-46A5BCFB9B69
language of work or name	English
cites work	wds:Q57022926-074BE5A4-B75C-4B40-936B-58A862700910 wds:Q57022926-0F24FF0E-2CB0-4EB8-A069-125591DF198D wds:Q57022926-200EC800-1424-4025-9148-9A86F028B90A wds:Q57022926-46604ED5-D373-43D3-AA35-242FB6777341 wds:Q57022926-5CCB054A-6B41-49ED-9580-0A9B8ECCC217 wds:Q57022926-67E7793E-A2F2-4E63-91D3-24E30073A54B wds:Q57022926-6911627C-108B-4EAF-AFD7-066975A887BE wds:Q57022926-6BE973B1-A18E-4BBE-A93B-D64A84813821 wds:Q57022926-770FE33B-8EFA-4D0F-A3A6-8D191F6C76E2 wds:Q57022926-796ED9DA-9B8D-450F-A2F7-5ABF743AC992 wds:Q57022926-92F10DB4-4D5F-4E07-9329-D3144247B9F2 wds:Q57022926-967D7AE4-D20E-44B5-8434-CE3BE730B315 wds:Q57022926-9D12ED4B-3998-49A6-A617-3F727C1CEA04 wds:Q57022926-A1A0CD47-9B23-4A6F-B5EF-CA4E07FB58D4 wds:Q57022926-ACEADCAE-A49C-4981-91F8-319D9B097D50 wds:Q57022926-E117E70D-DFED-46BA-BF50-5A0D53E3C8E6 wds:Q57022926-E5DD2490-FF2F-440F-A1EA-29DF8752C0F0 wds:Q57022926-F201617E-0751-4C7D-804F-27E1F70C8406 wds:Q57022926-F442F906-2DA0-4F5B-AE2A-6A434A9C2960
cites work	Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation Comparison and evaluation of methods for liver segmentation from CT datasets. Tissue segmentation of head and neck CT images for treatment planning: a multiatlas approach combined with intensity modeling. Auto-segmentation of normal and target structures in head and neck CT images: a feature-driven model-based approach. Atlas-based auto-segmentation of head and neck CT images Medical image analysis. Automatic segmentation of head and neck CT images for radiotherapy treatment planning using multiple atlases, statistical appearance models, and geodesic active contours Deep Learning in Medical Image Analysis Deep feature learning for knee cartilage segmentation using a triplanar convolutional neural network Contour-Driven Atlas-Based Segmentation Sensitivity of salivary glands to radiation: from animal models to therapies A survey on deep learning in medical image analysis Clinical evaluation of atlas and deep learning based automatic contouring for lung cancer. Survey on deep learning for radiotherapy Minimizing second cancer risk following radiotherapy: current perspectives Artificial intelligence in radiation oncology: A specialty-wide disruptive transformation? SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation Segmentation of organs-at-risks in head and neck CT images using convolutional neural networks. Evaluation of segmentation methods on head and neck CT: Auto-segmentation challenge 2015.
author name string	wds:Q57022926-06323B77-518D-45BC-B118-680F14CB61F1 wds:Q57022926-1C62D0AB-0563-4C85-A93D-1640E8D96617 wds:Q57022926-407BB7AB-4754-4034-A895-7FAE8E5CF420 wds:Q57022926-41CBEC45-9521-49E8-89E6-55860400668F wds:Q57022926-A3FD76C4-CD57-4976-AE50-1F9A1F7119A1 wds:Q57022926-B8BA9138-2D26-4F0A-A7DD-5BCCA235E40D wds:Q57022926-C160211D-9A7C-491E-A837-9352A5E3BD74 wds:Q57022926-D059EF3C-5EC7-43A5-B181-089E0B6C4A45
author name string	Jan Klein Horst K Hahn Volker Dicken Tobias Gass Benjamin Haas Tomasz Morgas Michael Schwier Annika Hänsch
rdfs:label	Evaluation of deep learning methods for parotid gland segmentation from CT images (en) Evaluation of deep learning methods for parotid gland segmentation from CT images (nl)
skos:prefLabel	Evaluation of deep learning methods for parotid gland segmentation from CT images (en) Evaluation of deep learning methods for parotid gland segmentation from CT images (nl)
name	Evaluation of deep learning methods for parotid gland segmentation from CT images (en) Evaluation of deep learning methods for parotid gland segmentation from CT images (nl)
author	wds:Q57022926-ACE02646-59E8-4700-837A-236636492BC6
author	Hans Meine
title	wds:Q57022926-5FAC45A9-F2AA-49C1-B594-0DA534354ADD
title	Evaluation of deep learning methods for parotid gland segmentation from CT images (en)
page(s)	wds:Q57022926-BF937DC9-A310-4E05-9EDA-225D05B973B6
page(s)	011005
instance of	wds:Q57022926-9B60F701-6470-474B-87D8-494B1214B7B4
instance of	scholarly article
main subject	wds:Q57022926-790E8D27-7EA3-4767-880E-C7C52221FC7F
main subject	deep learning
PubMed ID	wds:Q57022926-55FEEE48-16A5-478B-BB3C-3CDB96DDD546
PubMed ID	http://rdf.ncbi.nlm.nih.gov/pubchem/reference/30276222
PubMed ID	30276222
published in	wds:Q57022926-4794FF80-FB15-425C-831C-34908AFEC515
published in	Journal of Medical Imaging
issue	wds:Q57022926-8AB0C6C3-A415-40FE-ADA2-7CEB1A37FEDE
volume	wds:Q57022926-7F332DBD-E5D2-426D-A68F-05107E02CD7D
issue	1
volume	6
DOI	wds:Q57022926-AD2246FD-079D-4493-BD6A-A57019157BD2
DOI	http://dx.doi.org/10.1117/1.JMI.6.1.011005
DOI	10.1117/1.JMI.6.1.011005
PMCID	wds:Q57022926-DED5C1C0-B31C-418E-8029-E54BBE9E141D
PMCID	6165912
is about of	https://www.wikidata.org/wiki/Special:EntityData/Q57022926

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