The paper proposes recovering all diffusion and chemotaxis parameters from the Fourier amplitudes of a single Turing pattern, but the uniqueness proof is incomplete and unvalidated.
Determining Sources in the Bioluminescence Tomography Problem
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abstract
In this paper, we revisit the bioluminescence tomography (BLT) problem, where one seeks to reconstruct bioluminescence signals (an internal light source) from external measurements of the Cauchy data. As one kind of optical imaging, the BLT has many merits such as high signal-to-noise ratio, non-destructivity and cost-effectiveness etc., and has potential applications such as cancer diagnosis, drug discovery and development as well as gene therapies and so on. In the literature, BLT is extensively studied based on diffusion approximation (DA) equation, where the distribution of peak sources is to be reconstructed and no solution uniqueness is guaranteed without adequate a priori information. Motivated by the solution uniqueness issue, several theoretical results are explored. The major contributions in this work that are new to the literature are two-fold: first, we show the theoretical uniqueness of the BLT problem where the light sources are in the shape of $C^2$ domains or polyhedral- or corona-shaped; second, we support our results with plenty of problem-orientated numerical experiments.
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Unveiling Biological Models Through Turing Patterns
The paper proposes recovering all diffusion and chemotaxis parameters from the Fourier amplitudes of a single Turing pattern, but the uniqueness proof is incomplete and unvalidated.