Deep Learning Methods for Anatomical Landmark Detection in Video Capsule Endoscopy Images.
AlexNet
Convolutional neural network
Gastrointestinal tract
GoogLeNet
Gradient-weighted class activation mapping (Grad-CAM)
ResNet
VGG-net
Video capsule endoscopy
Journal
Proceedings of the Future Technologies Conference (FTC) 2020. Future Technologies Conference (2020 : Online)
Titre abrégé: Proc Future Technol Conf (2020)
Pays: Switzerland
ID NLM: 101778462
Informations de publication
Date de publication:
Nov 2021
Nov 2021
Historique:
entrez:
25
10
2021
pubmed:
26
10
2021
medline:
26
10
2021
Statut:
ppublish
Résumé
Video capsule endoscope (VCE) is an emerging technology that allows examination of the entire gastrointestinal (GI) tract with minimal invasion. While traditional
Identifiants
pubmed: 34693407
doi: 10.1007/978-3-030-63128-4_32
pmc: PMC8528446
mid: NIHMS1696469
doi:
Types de publication
Journal Article
Langues
eng
Pagination
426-434Subventions
Organisme : NIDDK NIH HHS
ID : K23 DK117061
Pays : United States
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