MUSICAL – Multiple Signal Classification Algorithms

- Multi-option distributed computing solutions for super-resolution imaging

The MUSICAL technology

MUSICAL is an imaging software that makes super-resolution optical microscopy available to specialized labs and clinics as a high-end premium GPU or embedded solution, or to laymans with their own personal microscopy data through an budget-conscious cloud solution.

The technology can be applied to both super-resolution microscopy raw data as well as data generated by conventional low-cost microscopes. The key advantage it provides is not needing any calibration in illumination engineered microscopes or special dyes for achieving super-resolution.

MUSICAL processing method to exploit the high spatial frequencies of illumination pattern to generate super-resolved image. In other words, processing super-resolution images from microscopes at an immense speed.

The MUSICAL solutions

  • Cloud solution (Beta-stage)

Lightweight software for super-resolution imaging tailored to low-cost microscopes.

  • GPU solution (under development)

Plug-and-play dongle providing state-of-the-art imaging with an additional edge in processing time

  • Embedded solution (to be developed)

MUSICAL as a built-in hardware solution with the microscope. Unlocking it’s full imaging capabilities

Opportunities for collaboration

  • Licensees for MUSICAL cloud solution
  • Collaborative R&D with industrial partner for MUSICAL GPU or MUSICAL Embedded solution
  • Patent pending
As compared to diffraction-limited image on the left, MUSICAL reconstructs the cristae (i.e., the empty spaces between the outer and inner membranes of mitochondria) with amazing number of details using only 100 images of diffraction-limited video.

Collaboration partners

Universitetet i Tromsø

Contact information

Foto: Marius Fiskum

Lars Sørensen

Forretningsutvikler | Tech Transfer

lars@norinnova.no
Tlf. 942 45 511

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Spermotile – A sophisticated tool for improved fertilization success rate

Sperm filtration for improved success rate of assisted reproduction technology

About the technology

With current automated or manual IVF methods focusing on motility, the chance of identifying a sperm for fertilization is high, but the likelihood of the selected sperm being the best is small. This means an inaccurate quality analysis that takes a toll on success rate and asks for multiple fertilization attempts.

Spermotile solves this issue by an ‘all-rounder’ sperm selection criterion that is morphologically healthy, motile and demonstrates desirable dynamic behavior, enabling that the sperms picked are of indeed high quality and highly likely to result into success in the first attempt. In turn, it translated to better throughput and leaner operating costs.

Value proposition

The spermotile is an end-to-end solution for selecting the best sperm automatically in terms of motility, morphology and behavior and performing the fertilization process with improved accuracy, efficiency, and success rate, while simultaneously providing a low-cost, ready to use, and low training option for the end user. Patent pending.

Opportunities for collaboration

  • Development and testing of Spermotile
  • Pilot-testing with customers
Illustrated comparison between Spermotile and current solutions’ processing of filtering dead, non-progressive, and haphazard semen to isolate the best quality sperm. Current CASA solutions use phase contrast microscopy (PCM) to identify and analyse sperm, restricting analysis of advanced sperm motility.

Collaborators

Universitetet i Tromsø

Contact information

Foto: Marius Fiskum

Lars Sørensen

Forretningsutvikler | Tech Transfer

lars@norinnova.no
Tlf. 942 45 511

Les om andre prosjekter:

SPICE: Sea sPray ICE prediction model

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9. august 2023

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•
12. mai 2023

About the technology SMOLTR is a smolt-verification tool to be utilized in the smoltification process of salmon. Data indicates that this technology …

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– Based on the Aliivibrio wodanis chassis (PsyXpress) The challenge The main challenge in protein production is to achieve optimal solubility, activity …

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3. mai 2023

Instant volume microscopy The SOLIS Microscope A new type of fluorescence microscope that combines the best aspects of confocal with light-sheet microscopy. SOLIS …

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Novel and easy to use Deep Learning Input Function in dynamic PET scanning

- Deep Learning derived Input Function in dynamic PET

About the technology

With DLIF we present a non-invasive, automatically generated input-function for kinetic modelling in dynamic PET. Our deep learning models are trained end-to-end with dynamic PET images as input and ready-to-use input function as output. The model show very strong correlation and non-significant difference in influx (Ki) for myocardium and tumor derived with AIF and DLIF, respectively.

Value proposition

  • No surgery requirements
  • Compatible with any PET scanner and the most widely used tracers
  • Provides results that are highly accurate with less bias and variation than state of the art

Areas of application

  • Non-invasive input function for dynamic PET where blood sampling is not possible
  • Preclinical or clinical applications
  • Could be integrated into external software independent of PET scanner vendor
  • As a part of the PET scanner-software to deliver the DLIF together with the PET images

Resources and partners

  • The Norwegian Nuclear Medicine Consortium 180°N
  • Tromsø Research Foundation ​
  • Centre for Research-based Innovation (SFI) Visual Intelligence
  • Proof of concept validated for small scale research in mice

Comparison to state of the art technology

Image: Comparison model of DLIF and existing state of the art technology.

Opportunities for Collaboration

We are currently looking for industry partners who finds interest in our technology. We are open for working together on the development of DLIF to accommodate your needs.

Collaboration partners

Universitetet i Tromsø
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Contact information

Foto: Marius Fiskum

Ingrid Skjæveland

Forretningsutvikler | Tech Transfer

ingrid@norinnova.no
Tlf. 991 57 143

Les om andre prosjekter:

SPICE: Sea sPray ICE prediction model

•
11. august 2023

A tool that predicts ice amount and distribution on marine structures About the technology Due to climate changes the Arctic marine territories …

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•
9. august 2023

CYMOPLIVE – Cyto-Motility and Cyto-Plasticity in Vitro Live-Cell Assay About the technology Cymoplive is a platform that allows us to study cells …

, ,

SMOLTR – Synchronizing seawater readiness of salmon smolt with seawater transfer

•
12. mai 2023

About the technology SMOLTR is a smolt-verification tool to be utilized in the smoltification process of salmon. Data indicates that this technology …

PsyXpress, a unique protein expression platform

•
3. mai 2023

– Based on the Aliivibrio wodanis chassis (PsyXpress) The challenge The main challenge in protein production is to achieve optimal solubility, activity …

Single-objective light-sheet imaging system (SOLIS)

•
3. mai 2023

Instant volume microscopy The SOLIS Microscope A new type of fluorescence microscope that combines the best aspects of confocal with light-sheet microscopy. SOLIS …

, , ,

Microstructured Air-Suspended Thin-film (MAST) waveguide sensor

•
3. mai 2023

Superior gas monitoring and measurement Industry challenges Traditional gas sensing with absorption spectroscopy uses large multi-pass cells containing a sample gas, through …

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