  One of the significant steps in the process leading to the identification of
proteins is mass spectrometry, which allows for obtaining information about the
structure of proteins. Removing isotope peaks from the mass spectrum is vital
and it is done in a process called deisotoping. There are different algorithms
for deisotoping, but they have their limitations, they are dedicated to
different methods of mass spectrometry. Data from experiments performed with
the MALDI-ToF technique are characterized by high dimensionality. This paper
presents a method for identifying isotope envelopes in MALDI-ToF molecular
imaging data based on the Mamdani-Assilan fuzzy system and spatial maps of the
molecular distribution of peaks included in the isotopic envelope. Several
image texture measures were used to evaluate spatial molecular distribution
maps. The algorithm was tested on eight datasets obtained from the MALDI-ToF
experiment on samples from the National Institute of Oncology in Gliwice from
patients with cancer of the head and neck region. The data were subjected to
pre-processing and feature extraction. The results were collected and compared
with three existing deisotoping algorithms. The analysis of the obtained
results showed that the method for identifying isotopic envelopes proposed in
this paper enables the detection of overlapping envelopes by using the approach
oriented to study peak pairs. Moreover, the proposed algorithm enables the
analysis of large data sets.
