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Petr Vladimirovich Lebedev-Stepanov
Marina Eduardovna Buzoverya
Yulia Pavlovna Potekhina
Konstantin Olegovich Vlasov


Motivation: Endogenous intoxication (EI) is an integral pathology which gives the general information about state of health of the patient. There is a correlation of biochemical data (costly, require long-term invasive studies) and morphological indicators based on image analysis of the visual image of a droplet of saliva dried in standard conditions (a simple and cheap non-invasive procedure). It is important to develop cheap, fast, non-invasive, computerized morphological methods for a medical diagnostics of EI based on the unique clinical experience obtained in the past decade to apply for mass rapid screening and monitoring of patients during the clinical examination, and also for individual checkup the health of any patient.

Results: The method is proposed and laboratory setup is elaborated for determination of the EI by determination of morphological properties of dried pattern of evaporated saliva droplet. The set of microphotographs of the salivary dried patterns is formed taking into account the degree of endogenous intoxication. Criteria for expert evaluation of endogenous intoxication from images of saliva dried pattern image are proposed. For the first time, computer software was created and tested to determine the stage of endogenous intoxication.  These makes it possible to process a large number of digital images of saliva patterns, which allows evaluating the monitoring of the patients condition, and perform statistical processing of the data. Proposed method is a combination of bioinformatics and biochemistry approaches for obtaining diagnostic information from a morphological analysis of standardized dried patterns of biological liquid sessile drop.

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LEBEDEV-STEPANOV, Petr Vladimirovich et al. MORPHOLOGICAL ANALYSIS OF IMAGES OF DRIED DROPLETS OF SALIVA FOR DETERMINATION THE DEGREE OF ENDOGENOUS INTOXICATION. Journal of Bioinformatics and Genomics, [S.l.], n. 4 (9), nov. 2018. ISSN 2530-1381. Available at: <>. Date accessed: 11 dec. 2018. doi:
Bioimage informatics
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