Detecting cells in time varying intensity images in confocal microscopy for gene expression studies in living cells

In this work we present a time-lapsed confocal microscopy image analysis technique for an automated gene expression study of multiple single living cells. Fluorescence Resonance Energy Transfer (FRET) is a technology by which molecule-to-molecule interactions are visualized. We analyzed a dynamic series of ~102 images obtained using confocal microscopy of fluorescence in yeast cells containing RNA reporters that give a FRET signal when the gene promoter is activated. For each time frame, separate images are available for three spectral channels and the integrated intensity snapshot of the system. A large number of time-lapsed frames must be analyzed to identify each cell individually across time and space, as it is moving in and out of the focal plane of the microscope. This makes it a difficult image processing problem. We have proposed an algorithm here, based on scale-space technique, which solves the problem satisfactorily. The algorithm has multiple directions for even further improvement. The ability to rapidly measure changes in gene expression simultaneously in many cells in a population will open the opportunity for real-time studies of the heterogeneity of genetic response in a living cell population and the interactions between cells that occur in a mixed population, such as the ones found in the organs and tissues of multicellular organisms

Longitudinal Evaluation of Fatty Acid Metabolism in Normal and Spontaneously Hypertensive Rat Hearts with Dynamic MicroSPECT Imaging

The goal of this project is to develop radionuclide molecular imaging technologies using a clinical pinhole SPECT/CT scanner to quantify changes in cardiac metabolism using the spontaneously hypertensive rat (SHR) as a model of hypertensive-related pathophysiology. This paper quantitatively compares fatty acid metabolism in hearts of SHR and Wistar-Kyoto normal rats as a function of age and thereby tracks physiological changes associated with the onset and progression of heart failure in the SHR model. The fatty acid analog, 123I-labeled BMIPP, was used in longitudinal metabolic pinhole SPECT imaging studies performed every seven months for 21 months. The uniqueness of this project is the development of techniques for estimating the blood input function from projection data acquired by a slowly rotating camera that is imaging fast circulation and the quantification of the kinetics of 123I-BMIPP by fitting compartmental models to the blood and tissue time-activity curves

Design and Implementation of a Facility for Discovering New Scintillator Materials

We describe the design and operation of a high-throughput facility for synthesizing thousands of inorganic crystalline samples per year and evaluating them as potential scintillation detector materials. This facility includes a robotic dispenser, arrays of automated furnaces, a dual-beam X-ray generator for diffractometery and luminescence spectroscopy, a pulsed X-ray generator for time response measurements, computer-controlled sample changers, an optical spectrometer, and a network-accessible database management system that captures all synthesis and measurement data

Reconstruction of 4-D dynamic SPECT images from inconsistent projections using a Spline initialized FADS algorithm (SIFADS).

In this paper, we propose and validate an algorithm of extracting voxel-by-voxel time activity curves directly from inconsistent projections applied in dynamic cardiac SPECT. The algorithm was derived based on factor analysis of dynamic structures (FADS) approach and imposes prior information by applying several regularization functions with adaptively changing relative weighting. The anatomical information of the imaged subject was used to apply the proposed regularization functions adaptively in the spatial domain. The algorithm performance is validated by reconstructing dynamic datasets simulated using the NCAT phantom with a range of different input tissue time-activity curves. The results are compared to the spline-based and FADS methods. The validated algorithm is then applied to reconstruct pre-clinical cardiac SPECT data from canine and murine subjects. Images, generated from both simulated and experimentally acquired data confirm the ability of the new algorithm to solve the inverse problem of dynamic SPECT with slow gantry rotation

Deep learning image transformation under radon transform

Previously, we have shown that an image location, size, or even constant attenuation factor may be estimated by deep learning from the images Radon transformed representation. In this project, we go a step further to estimate a few other mathematical transformation parameters under Radon transformation. The motivation behind the project is that many medical imaging problems are related to estimating similar invariance parameters. Such estimations are typically performed after image reconstruction from detector images that are in the Radon transformed space. The image reconstruction process introduces additional noise of its own. Deep learning provides a framework for direct estimation of required information from the detector images. A specific case we are interested in is dynamic nuclear imaging, where the quantitative estimations of the target tissues are queried. Motion inherent in biological systems, e.g., in vivo imaging with breathing motion, may be modeled as a transformation in the spatial domain. Motion is particularly prevalent in dynamic imaging, while tracer dynamics in the imaged object are a second source of transformation in the time domain. Our neural network model attempts to discern the two types of transformation (motion and intensity variation dynamics), i.e., tries to learn one type of transformation, ignoring the other

Detecting cells in time varying intensity images in confocal microscopy for gene expression studies in living cells

In this work we present a time-lapsed confocal microscopy image analysis technique for an automated gene expression study of multiple single living cells. Fluorescence Resonance Energy Transfer (FRET) is a technology by which molecule-to-molecule interactions are visualized. We analyzed a dynamic series of ~102 images obtained using confocal microscopy of fluorescence in yeast cells containing RNA reporters that give a FRET signal when the gene promoter is activated. For each time frame, separate images are available for three spectral channels and the integrated intensity snapshot of the system. A large number of time-lapsed frames must be analyzed to identify each cell individually across time and space, as it is moving in and out of the focal plane of the microscope. This makes it a difficult image processing problem. We have proposed an algorithm here, based on scale-space technique, which solves the problem satisfactorily. The algorithm has multiple directions for even further improvement. The ability to rapidly measure changes in gene expression simultaneously in many cells in a population will open the opportunity for real-time studies of the heterogeneity of genetic response in a living cell population and the interactions between cells that occur in a mixed population, such as the ones found in the organs and tissues of multicellular organisms.This is a proceeding from Medical Imaging 2015: Digital Pathology 9420 (2015): 1, doi:10.1117/12.2081691. Posted with permission.</p

Clustering-initiated factor analysis application for tissue classification in dynamic brain positron emission tomography.

The goal is to quantify the fraction of tissues that exhibit specific tracer binding in dynamic brain positron emission tomography (PET). It is achieved using a new method of dynamic image processing: clustering-initiated factor analysis (CIFA). Standard processing of such data relies on region of interest analysis and approximate models of the tracer kinetics and of tissue properties, which can degrade accuracy and reproducibility of the analysis. Clustering-initiated factor analysis allows accurate determination of the time-activity curves and spatial distributions for tissues that exhibit significant radiotracer concentration at any stage of the emission scan, including the arterial input function. We used this approach in the analysis of PET images obtained using (11)C-Pittsburgh Compound B in which specific binding reflects the presence of β-amyloid. The fraction of the specific binding tissues determined using our approach correlated with that computed using the Logan graphical analysis. We believe that CIFA can be an accurate and convenient tool for measuring specific binding tissue concentration and for analyzing tracer kinetics from dynamic images for a variety of PET tracers. As an illustration, we show that four-factor CIFA allows extraction of two blood curves and the corresponding distributions of arterial and venous blood from PET images even with a coarse temporal resolution

Longitudinal Evaluation of Sympathetic Nervous System and Perfusion in Normal and Spontaneously Hypertensive Rat Hearts with Dynamic Single-Photon Emission Computed Tomography

The objective of this work was to evaluate the sympathetic nervous system and structure remodeling during the progression of heart failure in a rodent model using dynamic cardiac single-photon emission computed tomography (SPECT). The spontaneously hypertensive rat (SHR) model was used to study changes in the nervous system innervation and perfusion in the left ventricular (LV) myocardium with the progression of left ventricular hypertrophy (LVH) to heart failure. Longitudinal dynamic SPECT studies were performed with seven SHR and seven Wistar-Kyoto (WKY) rats over 1.5 years using a dual-head SPECT scanner with pinhole collimators. Time-activity curves (TACs) of the 123 I-MIBG and 201 Tl distribution in the LV blood pool and myocardium were extracted from dynamic SPECT data and fitted to compartment models to determine the influx rate, washout rate, and distribution volume (DV) of 123 I-MIBG and 201 Tl in the LV myocardium. The standardized uptake values (SUVs) of 123 I-MIBG and 201 Tl in the LV myocardium were also calculated from the static reconstructed images. The influx and washout rates of 123 I-MIBG did not show a significant difference between SHRs and WKY rats. The DVs of 123 I-MIBG were greater in the SHRs than in the WKY rats ( p = .0028). Specifically, the DV of 123 I-MIBG became greater in the SHRs by 6 months of age ( p = .0017) and was still significant at the age of 22 months. The SUV of 123 I-MIBG in SHRs exhibited abnormal values compared to WKY rats from the age of 18 months. There was no difference in the influx rate and the washout rate of 201 Tl between the SHRs and WKY rats. The SHRs exhibited greater DV of 201 Tl than WKY rats after the age of 18 months ( p = .034). The SUV of 201 Tl in SHRs did not show any significant difference from WKY at all ages. The higher DV of 123 I-MIBG in the LV myocardium reveals abnormal nervous system activity of the SHRs at an age of 6 months, whereas a greater DV of 201 Tl in the LV myocardium can only be detected at an age of 18 months. The results show that the abnormal nervous system activity appears earlier than perfusion. Furthermore, the comparison between the DV and the SUV indicates that dynamic SPECT with 123 I-MIBG and 201 Tl with the kinetic parameter DV is capable of detecting abnormalities of the LV at an early age