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.
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 Sciences. Dilip Prasad, also from the Department of Computer Sciences serves as deputy project manager.
The project includes the following collaborating departments:
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.