Image Processing Pipeline Improvements

Valo Health

Medical Device Software DevelopmentImage Processing


We partnered with Innolitics to improve and update our team’s analysis software. They have diligently worked to add new features and address the troubled areas of the code to both improve its efficiency, as well as its usability. They work independently solving problems and handling difficult coding situations to deliver quality changes and improvements. These improvements have streamlined our code into a more powerful and concise use interface.
Nate Bays, PhD

Nate Bays, PhD

Executive Director, Tissue Engineering at Valo Health

The Problem

Valo was using a set of in-house image-processing scripts to analyze experimental data for their biology pipelines. These scripts were inefficient and required their researchers to manually review the results. Valo was looking to find a software development partner to make these scripts more robust, streamlined, and scalable.

The Outcome

The solution enhances productivity by processing experiments at a rate >10x what was possible at the start of the project.

The Solution

Innolitics’s software engineers partnered with the Valo researchers to improve their processing pipeline. At each phase of the project, we understand user needs and focus our efforts on performance bottlenecks.

The major performance gains were accomplished through the combined effects of enhanced batch processing, incorporation of AI classifiers, and creation and streamlining to a universal GUI.

About Valo

Valo uses human data in the context of human disease to identify novel human disease-associated targets and biomarkers based on genotype-phenotype-causality linkages discovered through advanced machine learning techniques and Valo’s expert scientists. This allows Valo to approach treating human disease without using traditional surrogates like cell models, mice, or similar. There is no better way to understand humans and their diseases than humans themselves.

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