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In this article, we consider the problem of inverting the exponential Radontransform of a function in the presence of noise. We propose a kernel estimatorto estimate the true function, analogous to the one proposed by Korostel\"{e}vand Tsybakov in their article `Optimal rates of convergence of estimators in aprobabilistic setup of tomography problem', Problems of InformationTransmission, 27:73-81,1991. For the estimator proposed in this article, wethen show that it converges to the true function at a minimax optimal rate.

Minimax optimal estimator in the stochastic inverse problem for exponential Radon transform