DescriptionDynamic alteration in organelle morphology is an important indicator of cellular function and many efforts have been made to monitor the subcellular morphology. Optical scatter imaging (OSI), which combines light scattering spectroscopy with microscopic imaging, was developed to non-invasively track real-time changes in particle morphology in situ. Using a variable diameter iris as a Fourier spatial filter, the technique consisted of collecting images that encoded the intensity ratio of wide-to-narrow angle scatter (OSIR, optical scatter imaging ratio) at each pixel in the full field of view. For spherical particles, the OSIR was shown to decrease monotonically with diameter. In living cells, we reported this technique is able to detect mitochondrial morphological alterations, which were mediated by the Bcl-xL transmembrane domain, but could not be observed by fluorescence or DIC images. However, the initial design was based on Mie theory of scattering by spheres, and hence only adequate for measuring spherical particles. This limits the applicability of OSI to cellular functional studies involving organelles, which are naturally non-spherical. In this project, we aim to enhance the current capability of the existing optical scatter microscope to assess size and shape information for both spherical and non-spherical particles, and eventually apply this technique for monitoring and quantifying subcellular morphology within living cells. To reach this goal, we developed an improved system, in which the variable diameter iris is replaced with a digital micromirror device and adopted the concept of Gabor filtering to extend our assessment of morphology to the characterization of particle shape and orientation. Using bacteria and polystyrene spheres, we show how this system can be used to assess particle aspect ratio even when imaged at low resolution. We also show the feasibility of detecting alterations in organelle aspect ratio in situ within living cells. This improved OSI system could be further developed to automate morphological quantification and sorting of non-spherical particles in situ. In the future, we plan to pursue the assessment of morphology information for particles of arbitrary shape and seek to correlate gene expression and cell function with subcellular morphology, which may help in disease diagnosis and drug screening.