We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us
RANDOX LABORATORIES

Download Mobile App




AI Holography System Accurately Checks Quality of Red Blood Cells

By LabMedica International staff writers
Posted on 15 Aug 2022
Print article
Image: AI holography system checks blood quality without injections (Photo courtesy of Pexels)
Image: AI holography system checks blood quality without injections (Photo courtesy of Pexels)

Red blood cells are a major component of blood that carries oxygen. Red blood cells collected through blood donation are stored for a certain period of time until they are used for transfusion when needed. This process is necessary because unhealthy red blood cells do not function properly and may lead to fatal side effects such as acute lung damage. Conventionally, image-based red blood cell analysis technology is used, which is an invasive method that destroys the three-dimensional structure of red blood cells as red blood cells are observed after staining. In addition, there are technical limitations in rapidly analyzing state changes such as three-dimensional shape, density change, and motility characteristics of red blood cells. To overcome this problem, a research team has developed an AI holography system that automatically extracts important information and inspects the quality of red blood cells. The new system is expected to become a key technology for enabling cleaner and healthier red blood cell injections to patients through accurate quality inspection of red blood cells stored for a certain period of time for blood transfusion.

Scientists at Daegu Gyeongbuk Institute of Science and Technology (DGIST, Daegu, Korea) had earlier developed 'holography-based red blood cell division and classification technology.' However, this requires a number of pre-processing algorithms before analysis, which takes a long time, and involves difficulties in performing accurate analysis and classification. In response, the team successfully developed an AI holography system that automatically inspects the quality of red blood cells stored for a certain time by combining the 3D structure image data of red blood cells obtained with holography technology and generative adversarial neural network technology.

If the developed technology is used, it will be possible to automatically extract important values ​​of judgment for red blood cells by applying the automatic red blood cell 3D structural image analysis algorithm and also check its quality. In particular, it is possible to test the quality of red blood cells precisely and simply as there is no need for invasive methods or pre-treatment procedures required by existing technologies. It is expected to be used as a core technology to help minimize the side effects of transfusion by injecting clean and healthy red blood cells to patients needing blood transfusions.

“The technology developed through this research is the source technology that can automatically analyze how red blood cells, stored for transfusion, change their three-dimensional shape depending on the storage period and determine whether stored red blood cells are healthy red blood cells that can be transfused,” said Professor Moon In-kyu of the Department of Robotics and Mechatronics Engineering at DGIST who led the research team. “It is expected that it will help minimize the occurrence of side effects after transfusion in the future as it can check the state of stored red blood cells more minutely and test whether the red blood cells are safe for the patient before transfusion.”

Related Links:
DGIST 

Platinum Member
COVID-19 Rapid Test
OSOM COVID-19 Antigen Rapid Test
Magnetic Bead Separation Modules
MAG and HEATMAG
POCT Fluorescent Immunoassay Analyzer
FIA Go
New
Gold Member
Automatic Nucleic Acid Extractor
GeneRotex 24

Print article

Channels

Clinical Chemistry

view channel
Image: The 3D printed miniature ionizer is a key component of a mass spectrometer (Photo courtesy of MIT)

3D Printed Point-Of-Care Mass Spectrometer Outperforms State-Of-The-Art Models

Mass spectrometry is a precise technique for identifying the chemical components of a sample and has significant potential for monitoring chronic illness health states, such as measuring hormone levels... Read more

Immunology

view channel
Image: The novel test uses an existing diagnostic procedure as its basis to target the Epstein Barr Virus (Photo courtesy of 123RF)

Blood Test Measures Immune Response to Epstein-Barr Virus in MS Patients

Multiple sclerosis (MS) is a chronic neurological condition for which there is currently no cure. It affects around three million people globally and ranks as the second most common cause of disability... Read more

Microbiology

view channel
Image: The T-SPOT.TB test is now paired with the Auto-Pure 2400 liquid handling platform for accurate TB testing (Photo courtesy of Shutterstock)

Integrated Solution Ushers New Era of Automated Tuberculosis Testing

Tuberculosis (TB) is responsible for 1.3 million deaths every year, positioning it as one of the top killers globally due to a single infectious agent. In 2022, around 10.6 million people were diagnosed... Read more

Pathology

view channel
Image: Insulin proteins clumping together (Photo courtesy of Jacob Kæstel-Hansen)

AI Tool Detects Tiny Protein Clumps in Microscopy Images in Real-Time

Over 55 million individuals worldwide suffer from dementia-related diseases like Alzheimer's and Parkinson's. These conditions are caused by the clumping together of the smallest building blocks in the... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.