Multimodal Bioimaging

Narine Sarvazyan Armeni

Head of Laboratory

Professor, Foreign Member of NAS RA

The Multimodal Bioimaging laboratory has a broad research agenda built around two core themes. The first centers on next-generation hyperspectral imaging (HSI). Here, the aim is to move beyond the conventional three-dimensional HSI approach by introducing an additional dimension that includes excitation wavelengths. Currently the team is validating this new Multi-Excitation HSI (ME-HSI) approach across different biological targets. The new computational methods and software tools are being created to enable real-time processing and interpretation of the resulting ME-HSI datasets.

The second major line of work is in the field of tissue engineering. The laboratory team is working on developing collagen-based patches analogous to currently available commercial biomaterials. Research efforts are focused on identifying suitable local sources, refining isolation protocols, and producing constructs with superior mechanical strength, high biocompatibility, and strong regenerative potential. Several collagen isolation workflows have been systematically compared to assess their influence on scaffold microstructure, with lyophilized samples tested for their immunological properties. Future studies are planned in collaboration with the bioprinting startup FOLDINK to fabricate multi-layered skin equivalents with improved functional properties and architecture that more closely resembles native skin. Input from clinical partners will be used to align these developments with unmet needs in Armenia’ wound management and skin repair products.

An additional new direction involving pulsed field ablation (PFA) is being explored. The custom made PFA generator that can deliver microsecond-scale pulses up to 2 kV was built. It serves as a novel platform for testing diverse PFA protocols on cardiac and non-cardiac tissues, a modality that is rapidly gaining acceptance in electrophysiology.

The research team of Multimodal Bioimaging laboratory is actively applying its newly developed ME-HSI approach (can be also called 4D-HSI) to a variety of biological targets. In addition to wet lab experiments, multiple computational pipelines for managing, visualizing, and quantitatively analyzing these large 4D datasets have been developed and validated. In November of 2025 members of the laboratory team presented three oral and two poster presentations during the international IEEE conference (WHISPERS, Barcelona). These presentations highlighted superior performance of the ME-HSI approach when compared to the conventional HSI.

Publications

1. Gabrielyan, Y., Hunanyan, A., Bezirganyan, S., Davtyan, L., Avetisyan, A., Sarvazyan, N., ... & Yeghiazaryan, V. Comparative Analysis of Deep Learning Methods for Classification of Ablated Regions in Hyperspectral Images of Atrial Tissue. IEEE Access. DOI: 10.1109/ACCESS.2025.3543122.

2. Sergei A. Fedotov, Andrei V. Stepanov, Galina A. Sakuta, Ivan S. Andreev, Marina S. Ivanova, Ekaterina V. Baidyuk. Ultrastructural Remodeling of Cardiomyocytes in Postinfarction Myocardium of Rats in the Late Stages of the Disease. J. Cytometry, Part A. https://doi.org/10.1002/cyto.a.24915.

3. Chilingaryan, N., Villarruel, F., Soghomonyan, T., Yeghiazaryan, V., & Sarvazyan, N. 4D hyperspectral imaging for intraoperative tissue classification. In Medical Imaging 2025: Clinical and Biomedical Imaging (Vol. 13410, pp. 255-260). SPIE.

4. Matosyan, N., Chilingaryan, N., Sarvazyan, N., & Yeghiazaryan, V. Spectral pixels as images: CNN-based pixel classification of 4D hyperspectral data for nerve and ligament differentiation. In Medical Imaging 2025: Image Processing (Vol. 13406, pp. 565-573). SPIE. https://doi.org/10.1117/12.3047194.

5. N. Matosyan, N. Chilingaryan, N. Sarvazyan and V. Yeghiazaryan. "Combining 4D Hyperspectral Imaging With CNN for Nerve and Ligament Differentiation," 2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI), Houston, TX, USA, 2025, pp. 1-5, doi: 10.1109/ISBI60581.2025.10981284.

6. Baidiuk. E., Sakuta G., Stepanov A., Fedotov S. P-03-018. Morpho-functional changes of cardiomyocyte mitochondria in postinfarction ventricularremodeling of rat hearts. FEBS Open Bio 15 (Suppl. 2) (2025), p. 84. DOI: 10.1002/2211-5463.7007p.84. https://febs.onlinelibrary.wiley.com/doi/epdf/10.1002/2211-5463.70071.

7. Chilingaryan, N., Gasparyan, A., & Sarvazyan, N. Multi-Excitation Hyperspectral Imaging Toward Improved Lichen Identification. 2025 15th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS). To appear.

8. Hunanyan, A., Ter-Petrosyan, N., Villarruel, F., Soghomonyan, T., Sarvazyan, N., Butavyan, A., & Yeghiazaryan, V. Deep Learning Classification of Ablated Atrial Tissue in Multi-Excitation Hyperspectral Images. 2025 15th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS). To appear.

9. Ter-Petrosyan, N., Hunanyan, A., Villarruel, F., Sarvazyan, N., Butavyan, A., & Yeghiazaryan, V. Comparative Analysis of Multi-Excitation Hyperspectral Image Configurations for Ablated Atrial Tissue Classification. 2025 15th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS). To appear.

10. Sergei A. Fedotov, Andrei V. Stepanov, Galina A. Sakuta, Mikhail L. Vorobev, Ekaterina V. Baidyuk. Functional Changes in Mitochondrial Subpopulations of Left Ventricular Cardiomyocytes in Post-Infarction Rats During the Subacute Stage of Remodeling. Front. Biosci. (Landmark Ed) 2026, 31(6), 47046. https://doi.org/10.31083/FBL47046 (registering DOI).