People working with the NLOM topics

People working with the NLOM topics

picture_nlom people

From the left Rajesh Kumlinear, Elisabeth Romijn and Magnus Borstad Lilledahl

txt_Clinical applications of nonlinear microscopy

Our research mainly focuses on the use of nonlinear optical microscopy (NLOM) in clinical applications.

The possibility of doing online microscopic of tissue in-vivo will open up many opportunities for improving many therapeutic procedures, improving diagnostics and understanding disease progression. The research is taking a multidisciplinary approach were we are combining imaging techniques, image compared to the lasers with wavelength around 400-500 which are typically used in conventional confocal e analysis and mechanical analysis to better understand the behavior and changes of tissue.

the team

Principal investigator

Magnus Lilledahl

Magnus Borstad Lilledahl, Associate professor

My main research interest lies in using optical methods, primarily nonlinear microscopy to study changes in the microscopic structure in various diseases to better understand the progression of the disease. Our interests lies in the entire value chain from develeopment of optical techniques, image and data analysis, biophysical and biomechanical modelling, and clinical correlation.

Doctoral students (PhD)

Rajesh Kumar

Rajesh Kumar, Postdoctoral Researcher

Kumar is currently working on using nonlinear microscopy to to characterize structural and chemical modifcation in osteoarthritis and atherosclerosis (second harmonic generation and coherent Raman microscopy and spectroscopy). Before joining our lab he worked for two years as a research assistant at St.Andrews University, Scotland, working on Raman spectroscopy and development of the fiber probe for in vivo Raman analysis. He received his masters degree in Photonics from Cochin University in India.

Elisabeth Romijn

Elisabeth Inge Romijn, PhD

Romijn holds a Master of sciencen in technical physics. She is developing image analysis methods for characterizing the 3D structure of collagen fibres from second harmonic generation images. To achieve robust quantitative data, several methods are incorporated: deconvolution, Fourier transform, ellipsoidal fitting and skeletonization techniques. The structural parameters will be compared to MRI imaging data and used biomechanical models.
23 May 2023