Interpretation and classification of mass spectra is usually performed using a list of peaks as their mathematical representation. This fact makes peak detection a bottleneck of mass spectra analysis, since quality and biological relevance of any results strongly depends on the accuracy of peak detection process. Many algorithms utilize intensity to differentiate between peaks and noise and thus bias the detection process to the high abundant peaks. However important information may also be contained in the lower-intensity peaks that are more difficult to discover. We present an algorithm specifically designed for detection of low-abundant peaks.