Cell Detection by Functional Inverse Diffusion and Nonnegative Group Sparsity

by Prof. Joakim Jaldén (KTH)

Thursday 3 Sept 2020, 13:00 → 14:00 Europe/Stockholm

AlbaNova Main Building

On August 28, 2018, a Stockholm-based biotech company launched a new product: The Mabtech IRISTM, a next-generation FluoroSpot and ELISpot reader. The reader is a machine designed to analyze a type of biomedical image-based assays that are commonly used in immunology to study cell responses. A contemporary use case involves the development of vaccines for SARS-CoV-2. At the heart of this machine is a positivity constrained groups sparsity regularized least squares optimization problem, solved with large scale optimization methods.

 

The presentation will outline the problem of analyzing FluoroSpot assays from a signal processing, physics, and optimization perspective and explain the methods we designed to solve it. The problem essentially amounts to counting, localizing and quantifying heterogeneous diffuse spots in an image. The solution involves components such as the development of a tractable linear model from the physical properties that govern the reaction-diffusion-adsorption-desorption process in the assay; the formulation of an inverse problem for source localization; the role of group sparsity in finding a plausible solution to an otherwise ill-posed problem; and how to efficiently solve the resulting 40 million variable optimization problem on a GPU.