The coherence-controlled holographic microscope (CCHM)1,2 is an innovative system particularly designed for quantitative phase imaging (QPI) and measurement of live cell dynamics.3 An achromatic off-axis interferometer based on the diffraction grating is used in CCHM. The spatial and temporal coherence of illumination can be widely varied, and in this way, imaging properties of the microscope are substantially modifiable. The coherence gating effect induced by low coherence makes possible formation of optical sections of the sample4 (in reflection mode) or imaging through turbid media5,6 (in transmission mode). Low coherence also improves lateral resolution and the imaging in general.7 For exploiting these effects, CCHM works with a broad polychromatic light source, which makes all the difference to other off-axis holographic microscopes usually equipped with a laser light source.8,9 This is because the high-coherence light source leads to the formation of unwanted artifacts in QPI as a consequence of coherence noise, random interferences, and diffraction of light. Low-coherence illumination, however, requires precise alignment and high stability of the system to be maintained during long-lasting time-lapse QPI studies of activity and reaction of living cells. And just these advantages stand for the contribution of CCHM to cell biology research. For alignment of highly sensitive interferometric systems, a secondary light source is often used. The interferometer state detection is carried out by an auxiliary detector10 or by a system of detectors.11–13 These methods are unsuitable for CCHM, because they would cause photo-toxic effect on living cells,10,11,13 and because the alignment of the many additional optical elements would be very complicated.12 For this reason, an original method based on the measurement of the modulus of the reconstructed holographic signal was elaborated for assessing the instrument state and guiding the optimization. The basic realignment three-dimensional algorithm (BReTA) method is suitable for CCHM because it does not require additional optical components and light sources. Moreover, it is amenable to full automation because the value of the reconstructed holographic signal is available from the online image processing and the operation can be robotized. Finally, the verification of the BReTA method applicability is presented.