Abstract

Correct catheter position is crucial to ensuring appropriate function of the catheter and avoid complications. This paper describes a dataset consisting of 50,612 image level and 17,999 manually labelled annotations from 30,083 chest radiographs from the publicly available NIH ChestXRay14 dataset with manually annotated and segmented endotracheal tubes (ETT), nasoenteric tubes (NET) and central venous catheters (CVCs).

Measurement(s)

Catheter Device

Technology Type(s)

Annotation

Sample Characteristic - Organism

Homo sapiens

Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.15113043

Details

Title
CLiP, catheter and line position dataset
Author
Tang Jennifer S N 1   VIAFID ORCID Logo  ; Seah Jarrel C Y 2   VIAFID ORCID Logo  ; Zia Adil 2   VIAFID ORCID Logo  ; Gajera Jay 3   VIAFID ORCID Logo  ; Schlegel, Richard N 3 ; Wong Aaron J N 4   VIAFID ORCID Logo  ; Gai Dayu 1 ; Su, Shu 1 ; Bose, Tony 5 ; Kok, Marcus L 6 ; Jarema Alex 2 ; Harisis, George N 2 ; Chris-Tin, Cheng 7   VIAFID ORCID Logo  ; Kavnoudias Helen 8   VIAFID ORCID Logo  ; Wang, Wayland 1 ; Stein, Anouk 9   VIAFID ORCID Logo  ; Shih, George 10 ; Gaillard, Frank 11   VIAFID ORCID Logo  ; Dixon, Andrew 2 ; Law, Meng 12   VIAFID ORCID Logo 

1  The Royal Melbourne Hospital, Department of Radiology, Melbourne, Australia (GRID:grid.416153.4) (ISNI:0000 0004 0624 1200) 
2  Alfred Health, Department of Radiology, Melbourne, Australia (GRID:grid.267362.4) (ISNI:0000 0004 0432 5259) 
3  Alfred Health, Melbourne, Australia (GRID:grid.267362.4) (ISNI:0000 0004 0432 5259) 
4  Monash Health, Department of Radiology, Melbourne, Australia (GRID:grid.419789.a) (ISNI:0000 0000 9295 3933); Barwon Imaging, Geelong, Australia (GRID:grid.419789.a) 
5  The Royal Melbourne Hospital, Melbourne, Australia (GRID:grid.416153.4) (ISNI:0000 0004 0624 1200) 
6  Eastern Health, Box Hill, Australia (GRID:grid.414366.2) (ISNI:0000 0004 0379 3501) 
7  Barwon Imaging, Geelong, Australia (GRID:grid.267362.4) 
8  Alfred Health, Department of Radiology, Melbourne, Australia (GRID:grid.267362.4) (ISNI:0000 0004 0432 5259); Monash School of Medicine, Nursing and Health Sciences, Department of Surgery, Clayton, Australia (GRID:grid.267362.4) 
9  MD.ai, New York, USA (GRID:grid.416153.4) 
10  Weill Cornell Medicine, Department of Radiology, New York, USA (GRID:grid.5386.8) (ISNI:000000041936877X) 
11  The Royal Melbourne Hospital, Department of Radiology, Melbourne, Australia (GRID:grid.416153.4) (ISNI:0000 0004 0624 1200); Faculty of Medicine, Dentistry and Health Sciences at the University of Melbourne, Melbourne, Australia (GRID:grid.1008.9) (ISNI:0000 0001 2179 088X) 
12  Alfred Health, Department of Radiology, Melbourne, Australia (GRID:grid.267362.4) (ISNI:0000 0004 0432 5259); Monash University, Department of Electrical and Computer Systems Engineering, Clayton, Australia (GRID:grid.1002.3) (ISNI:0000 0004 1936 7857); Nursing and Health Sciences, Department of Neuroscience, Monash School of Medicine, Clayton, Australia (GRID:grid.1002.3); University of Southern California, Departments of Neurological Surgery and Biomedical Engineering, Los Angeles, USA (GRID:grid.42505.36) (ISNI:0000 0001 2156 6853) 
Publication year
2021
Publication date
2021
Publisher
Nature Publishing Group
e-ISSN
20524463
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41597-021-01066-8
ProQuest document ID
2587505295
Copyright
© Crown 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.