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

05/04/2021
by   Sagi Eppel, et al.
3

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. This work presents a new dataset containing 1,300 annotated images of medical samples involving vessels containing liquids and solid material. The images are annotated with the type of liquid (e.g., blood, urine), the phase of the material (e.g., liquid, solid, foam, suspension), the type of vessel (e.g., syringe, tube, cup, infusion bottle/bag), and the properties of the vessel (transparent, opaque). In addition, vessel parts such as corks, labels, spikes, and valves are annotated. Relations and hierarchies between vessels and materials are also annotated, such as which vessel contains which material or which vessels are linked or contain each other. Three neural networks are trained on the dataset: One network learns to detect vessels, a second net detects the materials and parts inside each vessel, and a third net identifies relationships and connectivity between vessels.

READ FULL TEXT

page 1

page 2

page 3

page 4

page 6

page 9

page 10

page 11

research
01/20/2015

Tracing the boundaries of materials in transparent vessels using computer vision

Visual recognition of material boundaries in transparent vessels is valu...
research
01/31/2016

Tracing liquid level and material boundaries in transparent vessels using the graph cut computer vision approach

Detection of boundaries of materials stored in transparent vessels is es...
research
03/08/2023

Medical Waste Sorting: a computer vision approach for assisted primary sorting

Medical waste, i.e. waste produced during medical activities in hospital...
research
09/12/2021

U-Net Convolutional Network for Recognition of Vessels and Materials in Chemistry Lab

Convolutional networks have been widely applied for computer vision syst...
research
01/11/2023

A new sampling methodology for creating rich, heterogeneous, subsets of samples for training image segmentation algorithms

Creating a dataset for training supervised machine learning algorithms c...
research
10/14/2017

Hierarchical semantic segmentation using modular convolutional neural networks

Image recognition tasks that involve identifying parts of an object or t...

Please sign up or login with your details

Forgot password? Click here to reset