TY  - JOUR
AU  - Kucarov, Marianna Dimitrova
AU  - Szakállas, Nikolett
AU  - Molnár, Béla
AU  - Kozlovszky, Miklós
TI  - Enhanced Tumor Diagnostics via Cyber-Physical Workflow: Integrating Morphology, Morphometry, and Genomic MultimodalData Analysis and Visualization in Digital Pathology
JF  - SENSORS
J2  - SENSORS-BASEL
VL  - 25
PY  - 2025
IS  - 14
PG  - 33
SN  - 1424-8220
DO  - 10.3390/s25144465
UR  - https://m2.mtmt.hu/api/publication/36271828
ID  - 36271828
AB  - The rapid advancement of genomic technologies has significantly transformed biomedical research and clinical applications, particularly in oncology. Identifying patient-specific genetic mutations has become a crucial tool for early cancer detection and personalized treatment strategies. Detecting tumors at the earliest possible stage provides critical insights beyond traditional tissue analysis. This paper presents a novel cyber-physical system that combines high-resolution tissue scanning, laser microdissection, next-generation sequencing, and genomic analysis to offer a comprehensive solution for early cancer detection. We describe the methodologies for scanning tissue samples, image processing of the morphology of single cells, quantifying morphometric parameters, and generating and analyzing real-time genomic metadata. Additionally, the intelligent system integrates data from open-access genomic databases for gene-specific molecular pathways and drug targets. The developed platform also includes powerful visualization tools, such as colon-specific gene filtering and heatmap generation, to provide detailed insights into genomic heterogeneity and tumor foci. The integration and visualization of multimodal single-cell genomic metadata alongside tissue morphology and morphometry offer a promising approach to precision oncology.
LA  - English
DB  - MTMT
ER  -