Quantitative multi-parametric analysis of biological imaging is fast emerging as a crucial area in biomedical research. This progress towards increasingly advanced image analysis is made possible by the confluence of molecular and cell biology, microscopy (and nanoscopy), image processing algorithms and data science within a single biomedical image analysis workflow (shown in the figure).
Currently, New Zealand researchers are doing high quality biomedical imaging through many different modalities. However, the image processing and data analysis parts are mostly low throughput and manual. Collaboration between the different discplines to improve the image analysis workflows is largely ‘ad-hoc’ and many biological researchers are not familiar with the ‘state of the art’ in the other domains (e.g. advanced image processing algorithms for better object segmentation and parametrization or machine learning mediated automatic classification of objects or unsupervised clustering of objects in multidimensional space to identify new patterns and clusters).
In 2018, the BIRU at the University of Auckland spearheaded the Network of BioMedical Image Analysis (NoBIAs). This network aims to facilitate interaction between researchers from biomedical sciences, computer science and data science. The network will serve as a forum for the researchers to discuss analysis related issues and problems that they are facing. In addition, the group can share image processing algorithms or ideas that have helped in past image analyses as well.
The hope is that this discussion would promote innovative and better image analysis of the large volumes of data generated. The discussions may also then evolve into more concrete collaborations over time. The meetings will be once every 2-3 months (or monthly) initially. We also aim to incorporate a web-based forum (or a mailing list) as an additional channel of communication. While the NoBIAs is being incubated by BIRU at The University of Auckland, it aims to be an inclusive network and will welcome members from outside the University as well.
