Dr. Mehdi Alizadeh Profile

Dr. Mehdi Alizadeh

at Vilnius Univ

SPIE Involvement:

Author

Publications (6)

Proceedings Article | 6 June 2024 Poster

Visualizing densely interwoven fiber networks in biological tissues using Computational Scattered Light Imaging

Loes Ettema, Hamed Abbasi, Viktoras Mazeika, Mehdi Alizadeh, Virginijus Barzda, Miriam Menzel

Proceedings Volume PC12996, PC1299616 (2024) https://doi.org/10.1117/12.3016664

KEYWORDS: Scattered light, Biological imaging, Visualization, Tissues, Voxels, Microscopy, Light emitting diodes, Image resolution, Biological samples, Signal intensity

Proceedings Article | 13 March 2024 Presentation

Origin of collagen chiral response in polarimetric second harmonic generation microscopy

Mehdi Alizadeh, Viktoras Mazeika, Danute Bulotiene, Vitalijus Karabanovas, Lukas Kontenis, Virginijus Barzda

Proceedings Volume PC12847, PC128470O (2024) https://doi.org/10.1117/12.3003060

KEYWORDS: Collagen, Second harmonic generation, Polarimetry, Microscopy, Laser radiation, Visualization, Statistical analysis, Diseases and disorders, Dichroic materials

Read Abstract +

Proceedings Article | 13 March 2024 Presentation

Disorder in collagen at the tumor boundary investigated with double Stokes-Mueller polarimetric microscopy

Viktoras Mažeika, Mykolas Mačiulis, Lukas Kontenis, Mehdi Alizadeh, Masood Samim, Serguei Krouglov, Edvardas Žurauskas, Virginijus Barzda

Proceedings Volume PC12854, PC128540J (2024) https://doi.org/10.1117/12.3002404

KEYWORDS: Polarimetry, Collagen, Diseases and disorders, Tumors, Second harmonic generation, Cooccurrence matrices, Nonlinear susceptibility, Mueller matrices, Tissues, Polarization

Read Abstract +

Proceedings Article | 30 May 2022 Presentation

Investigation of melanoma tissue with nonlinear multimodal polarimetric microscopy using texture analysis and machine learning

Martynas Riauka, Viktoras Mazeika, Mykolas Maciulis, Lukas Kontenis, Edvardas Zurauskas, Mehdi Alizadeh, Kamdin Mirsanaye, Virginijus Barzda

Proceedings Volume PC12144, PC121440S (2022) https://doi.org/10.1117/12.2621489

KEYWORDS: Polarimetry, Tissues, Melanoma, Collagen, Polarization, Microscopy, Second-harmonic generation, Machine learning, Statistical analysis, Microscopes

Read Abstract +

Development and metastasis of cancer are known to change the structure of extracellular matrix (ECM), which affect the tumor's further growth and spread. A substantial part of ECM is comprised of collagen, which is a noncentrosymmetric structure. As a result, it generates second harmonic signals, dependent on the polarization of incoming light. This property of collagen led to the applications of polarization-resolved second-harmonic generation (P-SHG) microscopy in investigating collagen ultrastructure changes in different cancers. In this work, multiphoton absorption fluorescence (MPF), third-harmonic generation (THG) and polarimetric second-harmonic generation (P-SHG) measurements were performed on various types and staging of human melanoma histological sections. Reduced polarimetry techniques, employing linear and circular polarization states, were used to obtain polarimetric SHG parameters of collagen in both normal and cancerous tissues. These parameters provide important information about the structural properties of collagen. The parameter distributions were analyzed using a grey-level co-occurrence matrix (GLCM), which allows to obtain statistical parameters, such as correlation, contrast, entropy, angular second moment and inverse difference moment. Statistical tests were performed on polarimetric and texture analysis data in order to determine whether parameter distribution differences in normal and cancerous tissues are statistically significant. Furthermore, a machine learning classifier algorithm was trained to distinguish normal tissues from cancerous using aforementioned polarimetric and texture parameters as predictors. Firstly, separate training and testing datasets were formed from each sample and classification was carried out for each of them individually and afterwards, a common training dataset was used for all samples. The results suggest that normal and cancerous skin tissues can be distinguished from each other with the help of multimodal nonlinear polarimetric microscopy. Also, depending on the type and stage of melanoma, the differences in some polarimetric and texture parameters are more pronounced, suggesting its possible application in melanoma diagnostics and differentiation.

Proceedings Article | 30 May 2022 Presentation

Revealing chirality of biological structures using different polarimetric SHG microscopy techniques

Mehdi Alizadeh, Viktoras Mažeika, Mykolas Maciulis, Martynas Riauka, Virginijus Barzda

Proceedings Volume PC12144, PC121440Z (2022) https://doi.org/10.1117/12.2621611

KEYWORDS: Collagen, Second-harmonic generation, Polarimetry, Microscopy, Numerical modeling, Microscopes, Harmonic generation, Dichroic materials, Detector development, Cancer

Read Abstract +

Showing 5 of 6 publications

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Keywords/Phrases

Search In:

Publication Years