Query
Anatomical location
Endoscopic ultrasound
Gastrointestinal stromal tumours
Object detection
Journal
Computers in biology and medicine
ISSN: 1879-0534
Titre abrégé: Comput Biol Med
Pays: United States
ID NLM: 1250250
Informations de publication
Date de publication:
01 2023
01 2023
Historique:
received:
13
09
2022
revised:
19
11
2022
accepted:
13
12
2022
pubmed:
22
12
2022
medline:
6
1
2023
entrez:
21
12
2022
Statut:
ppublish
Résumé
Gastrointestinal stromal tumour (GIST) lesions are mesenchymal neoplasms commonly found in the upper gastrointestinal tract, but non-invasive GIST detection during an endoscopy remains challenging because their ultrasonic images resemble several benign lesions. Techniques for automatic GIST detection and other lesions from endoscopic ultrasound (EUS) images offer great potential to advance the precision and automation of traditional endoscopy and treatment procedures. However, GIST recognition faces several intrinsic challenges, including the input restriction of a single image modality and the mismatch between tasks and models. To address these challenges, we propose a novel Query
Identifiants
pubmed: 36543005
pii: S0010-4825(22)01132-5
doi: 10.1016/j.compbiomed.2022.106424
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
106424Informations de copyright
Copyright © 2022 Elsevier Ltd. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.