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Our Work

We contribute to several large and small projects. It's a great opportunity to help visitors understand the context and background of your latest work. Following projects listed below are our groups large scale projects with public research grant ID in Cristin.


Virtual Stain

VirtualStain is an ambitious project that could have a far-reaching impact on the way we analyse and interpret tissue- and cell-images. This large, collaborative effort, involving four departments from three different faculties, is part of the UiT Tematiske satsninger, a funding program intended to encourage innovative interdepartmental and interdisciplinary projects.

VirtualStain will develop artificial intelligence (AI) tools to process, label and analyse microscopy and nanoscopy images of tissues and cells. This will make the time-consuming task of chemically staining (with noxious chemicals) such images obsolete. Applying AI to such a task will also enable researcher to image and label living tissues and cells, and follow them in real-time. New insights provided on tissue and cell function through these enhanced labelling and monitoring processes will allow for the development of complex and dynamic AI models of tissue and cells systems for use in medical research. VirtualStain is led by professor Alexander Horsch at the Department of Computer SciencesDilip Prasad, also from the Department of Computer Sciences serves as deputy project manager.

The project includes the following collaborating departments:

Organ Vision

OrganVision is a revolutionary technology proposition that will break new grounds in microscopy and develop an ideal imaging solution for organoid research. It will enable life scientists to visualize life unfolding in real-time inside the cells and tissue in an organ-mimicking living tissue environment (called organoid here). It will alter the paradigm in microscopy by converting the central obstacle of light scattering by thick samples into the central opportunity that enables 3D label-free imaging on organoids in real-time with sub-cellular (~200 nm) and inter-cellular resolution (~1 µm) at speeds of >1 volume per second (cube of 100 µm). 


For achieving this unprecedented feat, OrganVision will develop a new multi-physics solver that solves transport of intensity (ToI) and full wave electromagnetic (FWEM) models in a coupled manner. ToI provides 3D image with inter-cellular resolution and generates intensity distribution inside the sample. FWEM uses this intensity distribution to decode the near-field light interaction between the sub-cellular entities for generating 3D sub-cellular image. A novel microscope instrument delivers custom designed 3D illumination patterns at the speed of 200 patterns per second in order to solve the problem of ill-posedness encountered by these solvers. In order to exploit the opportunity thus created, OrganVision will develop an a computational model that models the dynamics and interactions of functional entities recorded by OrganVision imaging solution in order to identify the underlying mechanisms.

The proof-of-concept will be shown on engineered heart tissue for real-time imaging of cell and tissue activity towards studying injury, repair and regeneration in heart muscle. OrganVision will transform microscopy from a visualization device to a knowledge discovery tool that will change the course of organoid research forever. We believe that OrganVision will lead to better understanding and faster therapy for several diseases.


Nanoscale artificial intelligence in microscopy and nanoscopy for life sciences (NanoAI)

NanoAI is a novel approach of interpretable and analyzable artificial intelligence (AI) designed specifically for microscopy and nanoscopy (M&N) so that M&N can transform from a visualization device to a powerful knowledge discovery tool. NanoAI proposes a novel physics-based topology extractor that extracts compact topological
information about the biological structures from humongous M&N images and renders them amenable to easy interpretation and AI.


NanoAI will create a new research field at the nexus of artificial intelligence, physics, mathematics, technology, and biology, generating impact in each field of research. It brings extremely challenging problems of high societal relevance to AI and mathematics community, opens a new field of research and development for the delivery of the promised impact of M&N, and significantly broadens the horizon of possibilities for biological studies.


nanoVision is funded by EU EIC transition grant - towards lab to market. This is an innovation project in collaboration with Chip Nano Imaging AS, KTH, EMBL. 

Seeing is believing & understanding. Optical microscopes are still indispensable tools in life science and medicine after hundreds of year. The core value they hold is their capability to magnify and make small featurs visible, therefore serving as our windows into cells. For the same reason, there is a continuous motivation to improve their resolution, i.e. the smallest feature that can be visualized by a microscope. The invention of super-resolution optical microscopy (nanoscopy) has given us a glimpse of its impact in all fields of science and medical care. Imagine the new scientific discoveries that can be realized if every research and clinical laboratory is equipped with an optical nanoscope that can deliver super-resolution imaging enabling researchers a window to nanoscale biology. However, several pain points of the available solutions currently hinder wide scale penetration of optical nanoscopy, such as cost, complexity, small throughput, and limited flexibility.

NanoVision will fill this pressing gap in the market with an affordable, compact, multi-modal and high-throughput photonic-chip based optical nanoscopy. Present day nanoscope uses a "simple glass slide" to hold the sample and a "complex and bulky microscope set-up" to illuminate and image. We change the current paradigm to "a mass-producible photonic-chip" to hold and illuminate the sample and a "simple and compact optical microscope" to image it. Our radical idea is thus to take out laser light steering and delivery from the microscope and transfer it to a photonic-chip. Photonic-chip based nanoscopy improves the throughput by a factor of 100x besides reducing the cost by 2x, which will not only extend the present market of nanoscopy but could also open new market opportunities. An university spin-off from UiT, The Arctic University of Norway, Chip NanoImaging AS is commercializing this patentable technology (


MUSICAL toward innovation

This project has been funded by Digital Life Norway under Innovation Pilot program. The goal of this project to make MUSICAL available commercially via the cloud under the name MusiCloud. One person year has been funded for 2022-23.

We will soon be releasing the MUSICAL algorithm via webapp/browser.

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