We present the algorithm from our recent work Goncharov, Isaev, Novikov, Zaytsev (ArXiv preprint, 2024) for recovering a compactly supported function on $R_+$ from its Hankel transform given on a finite interval [0, r]. This work employs the PSWF-Radon approach that combines the theory of classical one-dimensional prolate spheroidal wave functions with the Radon transform theory, which was originally developed for reconstructing signals from their truncated Fourier transforms. Adapted to the Hankel transform, it achieves what is known as 'super-resolution' (the ability to recover details smaller than π/r), even in the presence of moderate noise in the data. In particular, our numerical examples show that the PSWF-Radon approach is consistently as good as, and often outperforms, the conventional approach that complements missing data with zeros. In this review, to illustrate the efficiency of our algorithm to simultaneously operate with the Hankel transform of several different orders, we also include a new application involving truncated multiple angle expansions for functions on $R^2$ .