Title |
A guide to human in vivo microcirculatory flow image analysis
|
---|---|
Published in |
Critical Care, February 2016
|
DOI | 10.1186/s13054-016-1213-9 |
Pubmed ID | |
Authors |
Michael J. Massey, Nathan I. Shapiro |
Abstract |
Various noninvasive microscopic camera technologies have been used to visualize the sublingual microcirculation in patients. We describe a comprehensive approach to bedside in vivo sublingual microcirculation video image capture and analysis techniques in the human clinical setting. We present a user perspective and guide suitable for clinical researchers and developers interested in the capture and analysis of sublingual microcirculatory flow videos. We review basic differences in the cameras, optics, light sources, operation, and digital image capture. We describe common techniques for image acquisition and discuss aspects of video data management, including data transfer, metadata, and database design and utilization to facilitate the image analysis pipeline. We outline image analysis techniques and reporting including video preprocessing and image quality evaluation. Finally, we propose a framework for future directions in the field of microcirculatory flow videomicroscopy acquisition and analysis. Although automated scoring systems have not been sufficiently robust for widespread clinical or research use to date, we discuss promising innovations that are driving new development. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Spain | 2 | 22% |
United Kingdom | 2 | 22% |
United States | 2 | 22% |
Peru | 1 | 11% |
Unknown | 2 | 22% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 5 | 56% |
Practitioners (doctors, other healthcare professionals) | 2 | 22% |
Science communicators (journalists, bloggers, editors) | 1 | 11% |
Scientists | 1 | 11% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | <1% |
United States | 1 | <1% |
Czechia | 1 | <1% |
Canada | 1 | <1% |
Unknown | 128 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 24 | 18% |
Student > Master | 20 | 15% |
Student > Ph. D. Student | 17 | 13% |
Student > Bachelor | 12 | 9% |
Other | 8 | 6% |
Other | 21 | 16% |
Unknown | 30 | 23% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 60 | 45% |
Engineering | 10 | 8% |
Agricultural and Biological Sciences | 7 | 5% |
Computer Science | 4 | 3% |
Biochemistry, Genetics and Molecular Biology | 4 | 3% |
Other | 10 | 8% |
Unknown | 37 | 28% |