The Kalman filter's role in optimizing fluorescence analysis

Abstract

This paper investigates the integration of the Kalman filter with fluorescence analysis in biomedical imaging, a synergy that holds the promise of advancing diagnostic accuracy and enhancing research methodologies in the study of biological systems. Employing a rigorous bibliometric analysis through VOSviewer, we explore the key trends, influential research clusters, and seminal publications that have marked the evolution of this interdisciplinary field. The Kalman filter, renowned for its predictive capabilities in real-time signal processing, emerges as a crucial tool for improving the signalto-noise ratio in fluorescence imaging, thereby facilitating the extraction of more accurate and meaningful data from complex biological phenomena. Our analysis reveals a dynamic and growing research landscape, where methodological advancements and computational challenges intersect with practical applications in biomedical imaging. By highlighting the significant contributions and identifying areas ripe for future investigation, this study underscores the potential of Kalman filter-enhanced fluorescence analysis to revolutionize biomedical diagnostics and imaging, offering new insights into cellular and molecular processes. Through this synthesis, we aim to provide a comprehensive overview of the current state of the art and to chart a course for the next wave of innovations in the field.