Abstract
Introduction: Clinical and medical laboratory experimentations in medical
research would require numerous repetitions to produce reliable and consistent
data. This experimentation required repetitions to capture medical imaging data
from the Ultrasound (U/S) machine coupled with precise localisation. Manual
analysis of raw data would be a laborious task and hinder experimental progress.
Objectives: The aim of this article is to evaluate the utilisation of artificial
intelligence (AI) image processing and robotics as part of experimentation method and subsequently to propose the utilisation of this tool as part of regular clinical laboratory methodology.
Methods: A robotic device was built to carry out repetitive tasks in our
experimentation of medical imaging. The motion of the robot was computer
controlled and incorporated images from a camera and a U/S machine. Data were processed using image processing algorithms thresholding and contour extraction to extract the region of interest automatically for further analysis. A laser line beam was attached to the machine to measure repeatability.
Results: Statistical analysis was carried out using the R language. The repeatability
of the machine had a standard deviation of 0.1499 and coefficient of variation
(COV) of 0.1562 with number of samples, n = 747, for a duration of 182 minutes.
Conclusion: Certain experimentation tasks involve repetitive action. AI
image processing and robotics provide tools to enhance work including colour
differentiation, motion tracking and time-series imaging data. Having utilised AI
in this experimentation, the use of AI as a tool is promoted to complement and
strengthen clinical research and medical science methodology.
research would require numerous repetitions to produce reliable and consistent
data. This experimentation required repetitions to capture medical imaging data
from the Ultrasound (U/S) machine coupled with precise localisation. Manual
analysis of raw data would be a laborious task and hinder experimental progress.
Objectives: The aim of this article is to evaluate the utilisation of artificial
intelligence (AI) image processing and robotics as part of experimentation method and subsequently to propose the utilisation of this tool as part of regular clinical laboratory methodology.
Methods: A robotic device was built to carry out repetitive tasks in our
experimentation of medical imaging. The motion of the robot was computer
controlled and incorporated images from a camera and a U/S machine. Data were processed using image processing algorithms thresholding and contour extraction to extract the region of interest automatically for further analysis. A laser line beam was attached to the machine to measure repeatability.
Results: Statistical analysis was carried out using the R language. The repeatability
of the machine had a standard deviation of 0.1499 and coefficient of variation
(COV) of 0.1562 with number of samples, n = 747, for a duration of 182 minutes.
Conclusion: Certain experimentation tasks involve repetitive action. AI
image processing and robotics provide tools to enhance work including colour
differentiation, motion tracking and time-series imaging data. Having utilised AI
in this experimentation, the use of AI as a tool is promoted to complement and
strengthen clinical research and medical science methodology.
| Original language | English |
|---|---|
| Pages | 53 |
| Number of pages | 1 |
| DOIs | |
| Publication status | Published - 2021 |
| Event | Medical & Health Week 2021 - Selangor, Malaysia Duration: 16 Aug 2021 → 27 Aug 2021 Conference number: 23rd |
Conference
| Conference | Medical & Health Week 2021 |
|---|---|
| Country/Territory | Malaysia |
| City | Selangor |
| Period | 16/08/21 → 27/08/21 |