Breaking diffraction limit of far-field imaging via structured illumination Bessel beam microscope (SIBM)

Breaking the diffraction limit in imaging microscopes with far-field imaging options has always been the thrust challenge for optical engineers and biologists over the years. Although structured illumination microscopy and Bessel beam assisted imaging has shown the capability of imaging with sub-diffraction resolutions, they rely on the use of objective lenses with large numerical apertures (NA). Hence, they fail to sustain resolutions at larger working distances. In this context, we demonstrate a method for nanoscale resolution imaging at longer working distances, named as Structured Illumination Bessel Microscopy (SIBM). The proposed method is envisaged for both biological and engineering applications that necessitate high imaging resolutions at large working distances.

Imaging behind opaque obstacle: a potential method for guided in vitro needle placement

We report a simple real time optical imaging concept using an axicon lens to image the object kept behind opaque obstacles in free space. The proposed concept underlines the importance and advantages of using an axicon lens compared to a conventional lens to image behind the obstacle. The potential of this imaging concept is demonstrated by imaging the insertion of surgical needle in biological specimen in real time, without blocking the field of view. It is envisaged that this proposed concepts and methodology can make a telling impact in a wide variety of areas especially for diagnostics, therapeutics and microscopy applications.

Quantitative non-invasive cell characterisation and discrimination based on multispectral autofluorescence features

Automated and unbiased methods of non-invasive cell monitoring able to deal with complex biological heterogeneity are fundamentally important for biology and medicine. Label-free cell imaging provides information about endogenous autofluorescent metabolites, enzymes and cofactors in cells. However extracting high content information from autofluorescence imaging has been hitherto impossible. Here, we quantitatively characterise cell populations in different tissue types, live or fixed, by using novel image processing and a simple multispectral upgrade of a wide-field fluorescence microscope. Our optimal discrimination approach enables statistical hypothesis testing and intuitive visualisations where previously undetectable differences become clearly apparent. Label-free classifications are validated by the analysis of Classification Determinant (CD) antigen expression. The versatility of our method is illustrated by detecting genetic mutations in cancer, non-invasive monitoring of CD90 expression, label-free tracking of stem cell differentiation, identifying stem cell subpopulations with varying functional characteristics, tissue diagnostics in diabetes, and assessing the condition of preimplantation embryos.