Acquisition of a ptychographic dataset typically requires the collection of a series of far field diffraction patterns as a function of probe position at the specimen plane. This can then be used to recover the complex specimen object function using either iterative or non-iterative algorithms. Importantly, ptychography is an inherently dose efficient technique, enabling effective the reconstruction of the exit wavefunction of radiation sensitive objects. For applications in the life sciences cryo-electron ptychography holds much promise particularly when used with a defocused probe to scan across a specimen with highly overlapped probe positions. This can be applied in a variant of conventional single particle analysis to provide 3D structures taking advantage of the known resolution variation of the effective ptychographic transfer function with convergence angle to provide wide spatial frequency bandwidth transfer. This geometry also allows datasets from wide fields of view to be collected that are suitable for studies of biologically relevant structures in a low concentration cellular context.Ultimately the resolution of reconstructions of radiation sensitive samples is limited by radiation damage which inherently scales with electron fluence and in general most Ptychographic datasets have extremely low signal to noise. Methods to overcome this will be discussed including sparse scan geometries optimised based on diffusion equations and the use of neural networks for processing of the raw input data. For the latter accurate centring of the bright field disk, data denoising and deconvolution of the detector MTF provides a typical 3-4 X enhancement of the SNR.
Finally, regularised and Fourier Ptychography as alternative data acquisition and processing strategies will be discussed.