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MINERVA

Mid- to Near Infrared Spectroscopy for Improved Medical Diagnostics

Taking advantage of several new breakthroughs in photonic technology to develop a new mid-IR technology platform and processes for early detection of cancer.

The final diagnosis of most types of cancers is performed by an expert clinician in anatomical pathology who examines suspicious tissue or cell samples extracted from the patient with a traditional optical microscope. Currently, this tedious and subjective assessment largely relies on the experience of the clinician and gives rise to suboptimal levels of discordance between different pathologists, especially in early stages of cancer development.

Recently, infrared (IR) spectroscopy has shown great potential to open a new chapter in the field of biomedical imaging. Mid-IR light is able to excite the vibrational modes of the most relevant biomolecules and the acquired signals inform about the chemical composition of the sample. Therefore, this emerging imaging technique has a high potential to perform objective pathological diagnoses and improve the detection and evaluation of the patient’s risk in screening and cancer surveillance.

To date, the lack of suitable sources, detectors and components in the mid-IR have restricted this technology to one of academic interest. The MINERVA project pursues several targets in parallel, from developing new IR instrumentation, such as fibre lasers, acousto-optic modulators, supercontinuum sources and detectors in the mid-IR range, to explore the performance and limitations of current IR spectroscopic technology in early cancer identification.

CVBLab group collaborates with other partners to explore and implement new mathematical and computational techniques from the interrelated fields of Digital Image Processing, Computer Vision, Machine Learning, Pattern Recognition, Multivariate Analysis and Chemometrics for the acquisition, processing and analysis of the bio-molecular spectral signatures of biological tissue and cells enclosed within IR hyperspectral images.

Agency

Comisión Europea bajo el Séptimo Programa Marco (FP7-317803)

Years

2012 to 2017

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