Visualization of parameter space for image analysis.

Image analysis algorithms are often highly parameterized and much human input is needed to optimize parameter settings. This incurs a time cost of up to several days. We analyze and characterize the conventional parameter optimization process for image analysis and formulate user requirements. With this as input, we propose a change in paradigm by optimizing parameters based on parameter sampling and interactive visual exploration. To save time and reduce memory load, users are only involved in the first step--initialization of sampling--and the last step--visual analysis of output. This helps users to more thoroughly explore the parameter space and produce higher quality results. We describe a custom sampling plug-in we developed for CellProfiler--a popular biomedical image analysis framework. Our main focus is the development of an interactive visualization technique that enables users to analyze the relationships between sampled input parameters and corresponding output. We implemented this in a prototype called Paramorama. It provides users with a visual overview of parameters and their sampled values. User-defined areas of interest are presented in a structured way that includes image-based output and a novel layout algorithm. To find optimal parameter settings, users can tag high- and low-quality results to refine their search. We include two case studies to illustrate the utility of this approach.

Nuclear morphology and deformation in engineered cardiac myocytes and tissues.

Cardiac tissue engineering requires finely-tuned manipulation of the extracellular matrix (ECM) microenvironment to optimize internal myocardial organization. The myocyte nucleus is mechanically connected to the cell membrane via cytoskeletal elements, making it a target for the cellular response to perturbation of the ECM. However, the role of ECM spatial configuration and myocyte shape on nuclear location and morphology is unknown. In this study, printed ECM proteins were used to configure the geometry of cultured neonatal rat ventricular myocytes. Engineered one- and two-dimensional tissue constructs and single myocyte islands were assayed using live fluorescence imaging to examine nuclear position, morphology and motion as a function of the imposed ECM geometry during diastolic relaxation and systolic contraction. Image analysis showed that anisotropic tissue constructs cultured on microfabricated ECM lines possessed a high degree of nuclear alignment similar to that found in vivo; nuclei in isotropic tissues were polymorphic in shape with an apparently random orientation. Nuclear eccentricity was also increased for the anisotropic tissues, suggesting that intracellular forces deform the nucleus as the cell is spatially confined. During systole, nuclei experienced increasing spatial confinement in magnitude and direction of displacement as tissue anisotropy increased, yielding anisotropic deformation. Thus, the nature of nuclear displacement and deformation during systole appears to rely on a combination of the passive myofibril spatial organization and the active stress fields induced by contraction. Such findings have implications in understanding the genomic consequences and functional response of cardiac myocytes to their ECM surroundings under conditions of disease.