Computer vision for liquid samples in hospitals and medical labs using hierarchical image segmentation and relations prediction

Understand

This work explores the use of computer vision for image segmentation and classification of medical fluid samples in transparent containers (for example, tubes, syringes, infusion bags).

• Handling fluids such as infusion fluids, blood, and urine samples is a significant part of the work carried out in medical labs and hospitals.
• The ability to accurately identify and segment the liquids and the vessels that contain them from images can help in automating such processes.
• Modern computer vision typically involves training deep neural nets on large datasets of annotated images.