On December 10th, Casper van Engelenburg graduated within the INSPiRED project on “Potential enrichments in malaria diagnostics: hyperspectral imaging and group-equivariant neural networks”. The first part of his MSc. research exploits hyperspectral imagery (HI) as new potential imaging modality of thin blood smears that could highly improve on preparation time, labor intensiveness and use of materials. In his thesis, the development and building of such a system is addressed and carried out. In the context of malaria, it is shown that HI is promising and lays a profound foundation for further exploration.
The design and evaluation of improved generalizing neural networks characterize the essence of the second and larger part of his MSc. research. Several group-equivariant networks are evaluated and compared with conventional convolutional networks which shows that efficient and redefined integration of weights can help build smarter and more robust classifiers for the detection of parasites. The full thesis can be found here.
