Holographic reconstruction method

A method for observing a sample, the sample lying in a sample plane defining radial positions, parameters of the sample being defined at each radial position, the method comprising:

• a) illuminating the sample using a light source, the light source emitting an incident light wave that propagates toward the sample;
• b) acquiring, with an image sensor, an image of the sample, said image being formed in a detection plane, the sample being placed between the light source and the image sensor;
• c) from the image acquired by the image sensor, obtaining an image of the sample, in the sample plane, the image of the sample in the sample plane corresponding to a distribution of at least one parameter of the sample in the sample plane;
• wherein c) comprises:
• (i) taking into account an initialization image, in the sample plane;
• (ii) applying a holographic propagation operator to the initialization image, or to a complex image of the sample resulting from (v) of a preceding iteration, so as to provide an estimated image, the estimated image being an estimation of the image acquired by the image sensor in the detection plane;
• (iii) comparing the image acquired in b) and the image estimated in (ii);
• (iv) depending on the comparison, updating the parameters of the sample;
• (v) provided that a convergence criterion has not been met or a preset number of iterations has not been reached, updating a complex image of the sample, in the sample plane, using the parameters of the sample updated in (iv), then reiterating (ii) to (v);
• (vi) using the parameters of the sample, resulting from the last step (iv) performed, to feed a supervised machine learning algorithm, so as to update parameters of the sample;
• (vii) using updated parameters of the sample resulting from (vi) to update the initialization image;
• (viii) reiterating, at least once, steps (ii) to (v), using, during the first reiteration, the updated initialization image resulting from (vii);
• (ix) obtaining an image of the sample from the parameters of the sample updated in step (iv) of the last iteration of steps (ii) to (v).