Computer Vision Application for Blood Recognition and Analysis

Project summary

The detection of white blood cells, quick extraction of features, and auto-generation of detailed clinical reports. A solution to process more slides with fewer compute resources to scale the workflow but not the budget.

We achieved a 10x faster speed of segmentation and classification of white blood cells, as well as automated, SVM-driven reporting – a practical, validated approach to drive laboratory efficiency.

Services:

CV development Mobile development

Overview

Project overview

Abto research and modeling experts created a medical imagery solution for a US customer dealing with breast cancer treatment. The software employs image classification and blood analysis to detect pathological tissue changes. This computer vision application works as a framework for white blood cell segmentation in microscopic blood images using digital image processing.

Customer: a US-based company, healthcare industry

Business outcome

Business value:

substantially decreased computational costs and overall expenses
achieved a 10 times increase in the operational speed

Project challenges:

to increase classification speed while preserving accuracy
to integrate a set of systems and subsystems interacting via text file into a single high-performing solution
to apply block processing for large TIFF files

Key features:

detection of certain blood cells on a huge image obtained by a microscope
input image features calculation by SVM classifier
automated report on blood cells characteristics

If you have a project idea, check out the rest of our computer vision expertise to see how we apply advanced image processing and video analysis to deliver value for our clients.

Tools & technology