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:
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 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.