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Defining fiber orientation at each voxel within a 3D biomedical image stack is potentially useful for a variety of applications, including cancer, wound healing and tissue regeneration. Current methods are typically computationally intensive or inaccurate. Herein, we present a 3D weighted orientation vector summation algorithm, which is a generalization of(More)
Active changes in mitochondrial structure and organization facilitate cellular homeostasis. Because aberrant mitochondrial dynamics are implicated in a variety of human diseases, their assessment is potentially useful for diagnosis, therapy, and disease monitoring. Because current techniques for evaluating mitochondrial morphology are invasive or(More)
Understanding the organization and mechanical function of the extracellular matrix (ECM) is critical for the development of therapeutic strategies that regulate wound healing following disease or injury. However, these relationships are challenging to elucidate during remodeling following myocardial infarction (MI) due to rapid changes in cellularity and an(More)
As neurodegenerative conditions are increasingly linked to mitochondrial dysfunction, methods for studying brain cell metabolism at high spatial resolution are needed to elucidate neurodegeneration mechanisms. Two-photon excited fluorescence (TPEF) imaging is a non-destructive, high-resolution technique for studying cell metabolism via endogenous(More)
Current methods for evaluating adipose tissue function are destructive or have low spatial resolution. These limit our ability to assess dynamic changes and heterogeneous responses that occur in healthy or diseased subjects, or during treatment. Here, we demonstrate that intrinsic two-photon excited fluorescence enables functional imaging of adipocyte(More)
Fiber-like structures are prevalent in biological tissues, yet quantitative approaches to assess their three-dimensional (3D) organization are lacking. We develop 3D directional variance, as a quantitative biomarker of truly 3D fibrillar organization by extending the directional statistics formalism developed for describing circular data distributions (i.e.(More)
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