Big Image Analytics

Our vision is utilize the latest Big Data and Deep Learning technology to extract meaningful, actionable information from images and videos


What we do

We are involved in the entire cycle from experiment design to measurement to analysis and interpretation. Pick and choose which components make the most sense for your needs.

We provide expertise in both static and dynamic X-ray imaging experiments on a wide variety of samples ranging from mouse bones to brain vasculature. We can help you design experiments, choose imaging modalities, scale up to large number of samples, and interpret the results in order to gain high quality, actionable information from imaging studies.
We have powerful, scalable in-house developed software for processing and extracting quantitative information in a streamlined fashion for even very large data sets. The software is automatically tested and verified to ensure the highest level of reliability for the results. We have the latest infrastructure available for storing and interactively analyzing thousands of samples with millions of microstructures. With our network analysis tools we can even investigate complicated networks of cells or pores with 10s of millions of connections.
We always deliver as a final product a detailed report distilling a series of complicated analyses into clear, legible figures and tables with thorough explanations of every step taken so the results can be reliably, automatically reproduced.

Our Products


Image Query Analysis Engine (IAQE) is our core platform for bringing the latest, scalable image analysis tools to end-users everywhere. The platform provides the ability to apply large complex operations across petabytes of data using simple commands. Beyond these commands, our tools make images search-able based on their content rather than meta-data in a real-time ad-hoc manner. Concretely this means that instead of manually going through archives of images processing them one at a time, you can search for images that have yellow cars, or X-rays with tumors larger than 5 cm, or satellite images which changed by more than 40% in the last two weeks. Behind the scenes, we leverage our cloud-based technology stack to robustly process these requests with stunning speed and efficiency.


Leveraging the large existing communities built around ImageJ and FIJI, Cloud Image Processing (CIP) lets you scale up these tools from one machine to hundreds in a distributed, fault-tolerant manner. Whether with powerful workstations, high-performance clusters, or cloud-based machines, our framework can handle your problem and make analysis and configuration easy using any device with our web-based tools.


With over 6 years experience in the large-scale image processing area we have experience with a large number of problems and techniques. Our experience ranges from biology to material science , from earth science and food engineering. Specifically we can help at any step of the analysis from experimental design to making sense of the results. Just contact us at info@4quant.com.


Image analysis is a diverse, complex field rife with caveats and constantly changing. We offer a number of training solutions ranging from theory and basic principals to specific tools and applications. These can be further personalized to match your exact needs and competences. Furthermore much of our material is available for free online through the course we developed at the Swiss Federal Institute of Technology entitled "Quantitative Big Imaging".

Our Technology

We have developed a range of image processing tools, called Spark Imaging Layer, on top of the latest Big Data framework, Apache Spark™. Spark provides a scalable, fault-tolerant, distributed backend for robustly handling large (giga-, tera-, and petabyte) datasets. Additionally we have cloud computing integration built-in meaning you can have a cluster in the cloud up and running in minutes, not days.


Rather than requiring complicated development, compiling and testing, our tools enable image analysis on thousands of images to be conducted interactively using a simple query language 4QL. Our extensions of the SQL language which we will reference as 4QL is fully SQL-99 compliant and offers all of our imaging functionality without requiring any developer experience.

Apache Spark

Spark is currently the world record holder for the fastest public-cloud sorting of a petabyte of data. It is one of the most active Apache projects with over 50 companies and 255 contributers and has even surpassed standard data processing frameworks such as NumPy, matplotlib, and SciKit-Learn.


Our platform is built from the ground up to support the most advanced Machine Learning and Deep Learning tools. TensorFlow is one of the most actively developed, flexible, and powerful machine learning platforms available. From object recognition to segmentation and feature extraction, it is unparalleled in the image analysis space and with our tools can easily scale to large image and video datasets. Our tools support the training, deployment and transfer-learning on models as well as combining the best parts of existing tools to solve complicated problems. We additionally provide higher-level access through our integration with libraries like Keras and sklearn to make building and validating models easy.

IBM Bluemix

Our software is intrinsically distributed and compatible with many cluster and cloud-based solutions to enable on-demand processing of large datasets without large infrastructure investements. For storing the data, we have out of the box support for local, Hadoop HDFS, Amazon S3™, and OpenStack Swift allowing for scalable, fault-tolerant storage of large datasets without the bottlenecks or hassle of storing everything on external hard drives. Leveraging the cloud computing infrastructure of IBM Bluemix and SoftLayer means we can focus on providing the best image analysis solutions and allow IBM to seamlessly manage the computational resources whether in the cloud or on-premise in a fully flexible and scalable manner. Finally our interactive web-based interfaces and notebooks make running and controlling complex image processing tasks on a cloud or cluster easy with any modern web browser.

Example Projects

We have worked on a number of projects in different fields varying from food research to bone microstructure. Below are a few selected projects which illustrate some of the capabilities we have.

4Quant Microstructure of cortical mouse bone

For bone microstructure we have developed workflows for automatically aligning and measuring cortical bone samples [1]. Futhermore we can perform detailed structural analysis of cortical and trabecular bone. We can even examine the shape, distribution, and alignment of osteocyte lacunae and blood vessels to assess the cellular level affect of genes, treatments, and disease models [2]. An example of how easy the analysis can be using our Image Query and Analysis Engine is shown in this worksheet. The results on over 1300 mice and terabytes of data have been published in BMC Genomics.


4Quant has given presentations at a number of conferences and workshops in areas from genetics to material science, machine learning, and big data. Selected presentations are available online

Real-time MRI image segmentation using parallel image computing and machine learning algorithms

Railway Track Diagnostics using inexpensive cameras and cloud computing

Flood Risk Modeling using ad-hoc queries on millions of satellite images

Reflective Buildings and Forested Region Quantification for quantifying regions, areas, and shapes in satellite images

Counting Cars Demo for counting and identifying the number of white cars in satellite images

Interactive Scientific Image Analysis and Analytics using Spark at the Spark East 2015 in New York City, NY

Scaling Up: Image Processing and Analytics using Spark at the Big Data Satellite Workshop at the X-Ray Microscopy Conference in Melbourne, Australia

High-throughput, Scalable, Quantitative, Cellular Phenotyping using X-Ray Tomographic Microscopy at International Work-Conference on Bioinformatics and Biomedical Engineering 2014 in Granada, Spain

Spark for High-throughput, Scalable, Quantitative Analysis of Genome-Scale Datasets at the Zurich Machine Learning Meetup in Zurich, Switzerland

Scaling Up Fast: Real-time Image Processing and Analytics using Spark at the Spark Summit 2014 in San Francisco, CA

An Introduction to Apache Spark at IBM Data Connect in Zurich, Switzerland

About Us

  • IBM Partner
  • ETH Spin-off

4Quant Ltd. is Spin-off of the ETH Zurich and the Paul Scherrer Institut based on the PhD Thesis of Kevin Mader done in the X-Ray Microscopy Laboratory of Marco Stampanoni. We are funded by the Pioneer Fellowship of the ETH Zurich and a member of the ETH Innovation and Entrepreneurship Lab. We are built on a strong foundation of partnerships ranging from the IBM Global Entrepreneur Program and Databricks for Cloud Support to SLS Techno Trans AG for access to the latest generation of imaging techniqes. We are committed to Open Source and have many of our projects available on Github and we push many of our latest developments back to the core project so the entire community can benefit from our developments.


We are located inside the Technopark Zurich on the first floor of the Einstein Wing. We can be reached by email at info@4quant.com or followed on Twitter