Automated Fourier space region-recognition filtering for off-axis digital holographic microscopy

Automated label-free quantitative imaging of biological samples can greatly benefit high throughput diseases diagnosis. Digital holographic microscopy (DHM) is a powerful quantitative label-free imaging tool that retrieves structural details of cellular samples non-invasively. In off-axis DHM, a proper spatial filtering window in Fourier space is crucial to the quality of reconstructed phase image. Here we describe a region-recognition approach that combines shape recognition with an iterative thresholding to extracts the optimal shape of frequency components. The region recognition technique offers fully automated adaptive filtering that can operate with a variety of samples and imaging conditions. When imaging through optically scattering biological hydrogel matrix, the technique surpasses previous histogram thresholding techniques without requiring any manual intervention. Finally, we automate the extraction of the statistical difference of optical height between malaria parasite infected and uninfected red blood cells. The method described here pave way to greater autonomy in automated DHM imaging for imaging live cell in thick cell cultures

Detection of leukocytes stained with acridine orange using unique spectral features acquired from an image-based spectrometer

A leukocyte differential count can be used to diagnosis a myriad blood disorders, such as infections, allergies, and efficacy of disease treatments. In recent years, attention has been focused on developing point-of-care (POC) systems to provide this test in global health settings. Acridine orange (AO) is an amphipathic, vital dye that intercalates leukocyte nucleic acids and acidic vesicles. It has been utilized by POC systems to identify the three main leukocyte subtypes: granulocytes, monocytes, and lymphocytes. Subtypes of leukocytes can be characterized using a fluorescence microscope, where the AO has a 450 nm excitation wavelength and has two peak emission wavelengths between 525 nm (green) and 650 nm (red), depending on the cellular content and concentration of AO in the cells. The full spectra of AO stained leukocytes has not been fully explored for POC applications. Optical instruments, such as a spectrometer that utilizes a diffraction grating, can give specific spectral data by separating polychromatic light into distinct wavelengths. The spectral data from this setup can be used to create object-specific emission profiles. Yellow-green and crimson microspheres were used to model the emission peaks and profiles of AO stained leukocytes. Whole blood was collected via finger stick and stained with AO to gather preliminary leukocyte emission profiles. A MATLAB algorithm was designed to analyze the spectral data within the images acquired using the image-based spectrometer. The algorithm utilized watershed segmentation and centroid location functions to isolate independent spectra from an image. The output spectra represent the average line intensity profiles for each pixel across a slice of an object. First steps were also taken in processing video frames of manually translated microspheres. The high-speed frame rate allowed objects to appear in multiple consecutive images. A function was applied to each image cycle to identify repeating centroid locations. The yellow-green (515 nm) and crimson (645 nm) microspheres exhibited a distinct separation in colorimetric emission with a peak-to-peak difference of 36 pixels, which is related to the 130 nm peak emission difference. Two AO stained leukocytes exhibited distinct spectral profiles and peaks across different wavelengths. This could be due to variations in the staining method (incubation period and concentration) effecting the emissions or variations in cellular content indicating different leukocyte subtypes. The algorithm was also effective when isolating unique centroids between video frames. We have demonstrated the ability to extract spectral information from data acquired from the image-based spectrometer of microspheres, as a control, and AO stained leukocytes. We determined that the spectral information from yellow-green and crimson microspheres could be used to represent the wavelength range of AO stained leukocytes, thus providing a calibration tool. Also, preliminary spectral information was successfully extracted from yellow-green microspheres translated under the linear slit using stationary images and video frames, thus demonstrating the feasibility of collecting data from a large number of objects

Numerical Model for the Determination of Erythrocyte Mechanical Properties and Wall Shear Stress in vivo From Intravital Microscopy.

The mechanical properties and deformability of Red Blood Cells (RBCs) are important determinants of blood rheology and microvascular hemodynamics. The objective of this study is to quantify the mechanical properties and wall shear stress experienced by the RBC membrane during capillary plug flow in vivo utilizing high speed video recording from intravital microscopy, biomechanical modeling, and computational methods. Capillaries were imaged in the rat cremaster muscle pre- and post-RBC transfusion of stored RBCs for 2-weeks. RBC membrane contours were extracted utilizing image processing and parametrized. RBC parameterizations were used to determine updated deformation gradient and Lagrangian Green strain tensors for each point along the parametrization and for each frame during plug flow. The updated Lagrangian Green strain and Displacement Gradient tensors were numerically fit to the Navier-Lame equations along the parameterized boundary to determined Lame's constants. Mechanical properties and wall shear stress were determined before and transfusion, were grouped in three populations of erythrocytes: native cells (NC) or circulating cells before transfusion, and two distinct population of cells after transfusion with stored cells (SC1 and SC2). The distinction, between the heterogeneous populations of cells present after the transfusion, SC1 and SC2, was obtained through principle component analysis (PCA) of the mechanical properties along the membrane. Cells with the first two principle components within 3 standard deviations of the mean, were labeled as SC1, and those with the first two principle components greater than 3 standard deviations from the mean were labeled as SC2. The calculated shear modulus average was 1.1±0.2, 0.90±0.15, and 12 ± 8 MPa for NC, SC1, and SC2, respectively. The calculated young's modulus average was 3.3±0.6, 2.6±0.4, and 32±20 MPa for NC, SC1, and SC2, respectively. o our knowledge, the methods presented here are the first estimation of the erythrocyte mechanical properties and shear stress in vivo during capillary plug flow. In summary, the methods introduced in this study may provide a new avenue of investigation of erythrocyte mechanics in the context of hematologic conditions that adversely affect erythrocyte mechanical properties

Infrared imaging spectroscopy of skin cancer lesions

Skin cancer is a disease of the twenty-first century since, unfortunately, being tan is associated to be healthy and good looking. UV radiation produces one of the most aggressive kinds of skin cancer: melanoma; once the damage is done there is no other solution that a rapid and effective diagnosis. Clinical examination and biopsies have shown to be slow and costly in many ways, so the possibility of getting a non-invasive optical detection of skin melanomas became a hot topic in biophotonics. In this context, multispectral imaging systems have approached the problem, but none of them worked inside the infrared range. Hence, this work has been proposed as an interesting, long-term project to further investigate about the possibilities of infrared imaging spectroscopy for the early detection of skin cancer through the development of such a system based on an InGaAs camera