Chapter

Computational Modeling of Objects Presented in Images. Fundamentals, Methods, and Applications

Volume 8641 of the series Lecture Notes in Computer Science pp 292-303

Computational Image Modeling for Characterization and Analysis of Intracellular Cargo Transport

  • Kuan-Chieh ChenAffiliated withDepartment of Biomedical Engineering, Carnegie Mellon UniversityCenter for Bioimage Informatics, Carnegie Mellon University
  • , Minhua QiuAffiliated withDepartment of Biomedical Engineering, Carnegie Mellon UniversityCenter for Bioimage Informatics, Carnegie Mellon UniversityGenomics Institute of the Novartis Research Foundation
  • , Jelena KovacevicAffiliated withDepartment of Biomedical Engineering, Carnegie Mellon UniversityCenter for Bioimage Informatics, Carnegie Mellon UniversityDepartment of Electrical Engineering, Carnegie Mellon University
  • , Ge YangAffiliated withDepartment of Biomedical Engineering, Carnegie Mellon UniversityCenter for Bioimage Informatics, Carnegie Mellon University

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Abstract

Active intracellular cargo transport is essential to survival and function of eukaryotic cells. How this process is controlled spatially and temporally so that the right cargo is delivered to the right destination at the right time remains poorly understood. To address this question, it is essential to characterize and analyze the molecular machinery and spatiotemporal behavior of intracellular transport. To this end, we developed related computational image models. Specifically, to study the molecular machinery of intracellular transport, we developed anisotropic spatial density kernels for reconstruction and segmentation of related super-resolution STORM (stochastic optical reconstruction microscopy) images. To study the spatiotemporal behavior of intracellular transport, we developed hidden Markov models and principal component analysis for representation and analysis of movement of individual transported cargoes. We validated and benchmarked the image models using simulated and actual experimental images. The models and related computational analysis methods developed in this study are general and can be used for studying molecular machinery and spatiotemporal dynamics of other cellular processes.

Keywords

image modeling intracellular transport spatiotemporal dynamics super-resolution imaging STORM imaging spatial density estimation hidden Markov model principal component analysis