Tomography Headquarters

left

X‑ray based tomography is already widely used in hospitals (CT) and in materials testing (microtomography), but its potential is much broader. With modern inverse problems methods,
imaging can be performed even with highly incomplete or low‑quality measurements, which makes it possible to replace expensive components with more affordable ones. Thanks to mathematics, tomography can also be carried out using methods other than X‑rays—for example, visible light, electric currents, magnetic fields, or combinations of these. Hyperspectral methods, meaning the use of deep color information, are also part of the research. The new types of devices are lightweight, portable, and reasonably priced to manufacture.

Examples of planned imaging solutions:

Electrical impedance tomography for stroke, enabling continuous monitoring of intensive‑care
patients.
Monitoring greenhouse gases and pollutant emissions in agriculture and process industry using
laser‑based tomography.
A new type of X‑ray tomography that utilizes subtle physical phenomena such as phase contrast. This improves image detail by a factor of 10,000.

The project is backed by Finland’s leading inverse mathematics community, which is among the world’s best in the field. TomoHQ teams operate across six organizations: Aalto University, the University of Helsinki, the Finnish Meteorological Institute, the University of Eastern Finland, LUT University, and the University of Oulu. The project’s researchers are physicists and mathematicians whose combined expertise covers the entire chain from theoretical mathematics and computational algorithms to measurement technology and industrial applications. TomoHQ creates many business opportunities: startups developing the technology, imaging services sold to customers, and licensing of new solutions to technology companies.

Goals

TomoHQ transforms imaging system design by replacing hardware-intensive, high-cost instruments with combinations of lower-cost sensors and advanced computational reconstruction. This shift to computation-driven imaging reduces capital costs, increases flexibility, and enables portable, embedded solutions that integrate directly into the user environment, supporting real-time monitoring, improved diagnostics, and data-driven decision making at the point of use.

The project unlocks value from multi-directional, multi-sensor, and multi-physics data by combining advanced mathematics, physics and AI-driven models. This enables high-resolution, reliable information extraction and creates new commercially viable sensing solutions.

In addition, the project aims to build capacity within Finnish industry, advance commercialization, and deliver societal impact alongside its research contributions.

right