The paper presents an algorithm based on low order statistics for the informative feature extraction for Raman spectroscopy data. The proposed method was tested on mouse preimplantation embryos Raman spectra. Both supervised and unsupervised machine learning methods were applied to selected the most informative features to test the separability of the processed data.
The paper presents the results of an in-vivo study of lymphedema tissue by optical coherent elastography in small animals. A lower limb lymphedema model in Wistar rats by lymph node resection was created. This article describes the application of the method of optical coherent elastography as a tool for in-vivo study of a model of lower limb lymphedema in small laboratory animals. Studies have shown that with the development of lymphedema, elastic properties change significantly.
A model of lymphedema in laboratory animals was realized and analyzed with multiphoton microscopy (MPM). Computer vision methods were used to describe the textures of lymphedema tissue MPM images, then informative features of the fibrosis development were extracted. Besides, the ratios of the autofluorescence lifetime to the second harmonic signal were estimated.
We applied the method of statistical trials to the parabolic equation of laser radiation propagation in biotissue to perform a new method of optical coherence tomography modeling. Results of modeling tests show the efficiency of the developed approach.
A model of lymphedema was developed using laboratory animals. During lymphatic edema enhancement, a study was made of changes in the structure of biological tissues by interference optical methods in the near infrared region of the spectrum. Statistical methods were applied for describing textures of the experimental images of the affected tissues, informative features of the dynamics of fibrosis development were identified.
Methods of two-photon microscopy are widely used in the study of biological objects, in particular, skin, due to the possibility to study objects both on the surface and at depth without attracting additional fluorophores due to endogenous autofluorescence. In this paper, the methods of image analysis of the AF signal and SHG signal are applied to assess the condition of the skin during the development of lymphedema. It is shown that for groups of healthy tissue and lymphedematous using SAAID distribution histograms, changes in tissues can be detected.
The quasi-static compression optical coherence elastography (OCE) is used to find Young’s modulus of human skin1,2 . The data on the layers of human skin deformation in vivo were obtained and analyzed. In the OCE compression method, a calibration layer with a known Young's modulus was used, which made it possible to identify the value of the volunteers' skin elastic modulus.
The method of laser IR radiation propagation simulation in a case of randomly inhomogeneous media based on Leontovich – Fock equation in the application of optical coherent tomography modeling in biotissues is proposed. We describe the proposed methodology and demonstrate its implementation on a test case.
The changes in the stiffness modulus of collagen structures in a collagen phantom were studied using optical coherent elastography (OCE). The disorganization of the phantom collagen fibers was obtained by mechanical action (twisting). Young's modulus values were measured for various phantom density values using the compression OCE method.
Last years the development of computer-aided diagnostic systems for medical image analysis has become a hot topic. A key step is connected with informative features extraction. Here, we discussed multiphoton microscopy and optical coherent tomography lymphedema tissue images analysis using gradient processing methods.
This work is devoted to the development of the approach to restoration of the spatial-temporal distribution of electric field in the human brain. This field was estimated from the model derived from the Maxwell’s equations with boundary conditions corresponding to electric potentials at the EEG electrodes, which are located on the surface of the head according to the standard “10-20” scheme. The MRI data were used for calculation of the spatial distribution of the electrical conductivity of biotissues in the human brain. The study of the electric field distribution using our approach was carried out for the healthy child and the child with autism. The research was carried out using the equipment of the Tomsk Regional Common Use Center of Tomsk State University.
Absorption spectra of paraffin-embedded prostate cancer and healthy tissues have been measured in the 0.2-3 THz range. The Principal Component Analysis and the Support Vector Machine (SVM) were applied to analyze experimental data. The SVM classifier was created which allows to distinguish the healthy tissues from tumor tissues, including classification of tumor tissue stage according to the Gleason scale.
KEYWORDS: Colorectal cancer, Blood, Plasma, Cancer, Simulation of CCA and DLA aggregates, Absorption, Terahertz radiation, Statistical analysis, Laser spectroscopy, Tumors
The study of exosomes of saliva and blood plasma by THz laser spectroscopy was carried out. Exosomes were sampled from patients with colorectal cancer (n = 6) and healthy volunteers (n = 5). A substantive examination of the samples absorption spectra was performed using the method of canonical correlation analysis. The presence of Glycine, LAlanine, Mannose was revealed everywhere. The Mannose content was less in exosomes samples corresponding to colorectal cancer in comparison with exosomes samples from healthy volunteers.
In our study we used rank-order filter, the emissions filter on the base of the criteria of Pearson, Gaussian filter and median filterfor improving the is fluorescence lifetime imaging microscopy (FLIM) data. The data obtained with the FLIM technology are the distribution with a pronounced peak, while during measurement the peak value is measured with an error. According to the analysisthe Gaussian filter is more useful to improve quality of FLIM data.Spatial filtering allows to reduce the noise component, obtained in the course of measurements, including reduction the influence of the individual bursts. Filtering in time scale allows to determine a peak value of intensity more accurately.This research was carried out using the equipment of Tomsk Regional Common Use Center of Tomsk State University.
The kernel construction for the biomedical data classification using Support Vector Machine based on Green function for Ornstein-Uhlenbeck equation is presented. Quantitative estimates of classification quality of exhaled air samples absorption spectra for patients with chronic obstructive pulmonary disease and healthy volunteers were carried out.
An approach to the reduction of the space of the absorption spectra, based on the original criterion for profile analysis of the spectra, was proposed. This criterion dates back to the known statistics chi-square test of Pearson. Introduced criterion allows to quantify the differences of spectral curves.
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