Biomedical subjects

B Roysam

Publications and source records attributed to B Roysam.

At least 19 recordsLinked to original sources

PubMed2006

Effects of insertion conditions on tissue strain and vascular damage during neuroprosthetic device insertion.

Long-term integration of neuroprosthetic devices is challenged by reactive responses that compromise the brain-device interface. The contribution of physical insertion parameters to immediate damage is not well described. We have developed an ex vivo preparation to capture real-time images of tissue deformation during device insertion using thick tissue slices from rat brains prepared with fluorescently labeled vasculature. Qualitative and quantitative assessments of damage were made for insertions using devices with different tip shapes inserted at different speeds. Direct damage to the vasculature included severing, rupturing and dragging, and was often observed several hundred micrometers from the insertion site. Slower insertions generally resulted in more vascular damage. Cortical surface features greatly affected insertion success; insertions attempted through pial blood vessels resulted in severe tissue compression. Automated image analysis techniques were developed to quantify tissue deformation and calculate mean effective strain. Quantitative measures demonstrated that, within the range of experimental conditions studied, faster insertion of sharp devices resulted in lower mean effective strain. Variability within each insertion condition indicates that multiple biological factors may influence insertion success. Multiple biological factors may contribute to tissue distortion, thus a wide variability was observed among insertions made under the same conditions.

Animals↗

PubMed2004

Topographically modified surfaces affect orientation and growth of hippocampal neurons.

Extracellular matrix molecules provide biochemical and topographical cues that influence cell growth in vivo and in vitro. Effects of topographical cues on hippocampal neuron growth were examined after 14 days in vitro. Neurons from hippocampi of rat embryos were grown on poly-L-lysine-coated silicon surfaces containing fields of pillars with varying geometries. Photolithography was used to fabricate 1 microm high pillar arrays with different widths and spacings. Beta(III)-tubulin and MAP-2 immunocytochemistry and scanning electron microscopy were used to describe neuronal processes. Automated two-dimensional tracing software quantified process orientation and length. Process growth on smooth surfaces was random, while growth on pillared surfaces exhibited the most faithful alignment to pillar geometries with smallest gap sizes. Neurite lengths were significantly longer on pillars with the smallest inter-pillar spacings (gaps) and 2 microm pillar widths. These data indicate that physical cues affect neuron growth, suggesting that extracellular matrix topography may contribute to cell growth and differentiation. These results demonstrate new strategies for directing and promoting neuronal growth that will facilitate studies of synapse formation and function and provide methods to establish defined neural networks.

Animals↗

PubMed2004

Genetics and imaging to assess oocyte and preimplantation embryo health.

Two major criteria are currently used in human assisted reproductive technologies (ART) to evaluate oocyte and preimplantation embryo health: (1) rate of preimplantation embryonic development; and (2) overall morphology. A major gene that regulates the rate of preimplantation development is the preimplantation embryo development (Ped) gene, discovered in our laboratory. In mice, presence of the Ped gene product, Qa-2 protein, results in a fast rate of preimplantation embryonic development, compared with a slow rate of preimplantation embryonic development for embryos that are lacking Qa-2 protein. Moreover, mice that express Qa-2 protein have an overall reproductive advantage that extends beyond the preimplantation period, including higher survival to birth, higher birthweight, and higher survival to weaning. Data are presented that suggest that Qa-2 increases the rate of development of early embryos by acting as a cell-signalling molecule and that phosphatidylinositol-32 kinase is involved in the cell-signalling pathway. The most likely human homologue of Qa-2 has recently been identified as human leukocyte antigen (HLA)-G. Data are presented which show that HLA-G, like Qa-2, is located in lipid rafts, implying that HLA-G also acts as a signalling molecule. In order to better evaluate the second criterion used in ART (i.e. overall morphology), a unique and innovative imaging microscope has been constructed, the Keck 3-D fusion microscope (Keck 3DFM). The Keck 3DFM combines five different microscopic modes into a single platform, allowing multi-modal imaging of the specimen. One of the modes, the quadrature tomographic microscope (QTM), creates digital images of non-stained transparent cells by measuring changes in the index of refraction. Quadrature tomographic microscope images of oocytes and preimplantation mouse embryos are presented for the first time. The digital information from the QTM images should allow the number of cells in a preimplantation embryo to be counted non-invasively. The Keck 3DFM is also being used to assess mitochondrial distribution in mouse oocytes and embryos by using the k-means clustering algorithm. Both the number of cells in preimplantation embryos and mitochondrial distribution are related to oocyte and embryo health. New imaging data obtained from the Keck 3DFM, combined with genetic and biochemical approaches, have the promise of being able to distinguish healthy from unhealthy oocytes and embryos in a non-invasive manner. The goal is to apply the information from our mouse model system to the clinic in order to identify one and only one healthy embryo for transfer back to the mother undergoing an ART procedure. This approach has the potential to increase the success rate of ART and to decrease the high, and undesirable, multiple birth rate presently associated with ART.

Animals↗

PubMed2003

Attenuation correction in confocal laser microscopes: a novel two-view approach.

Confocal microscopy is a three-dimensional (3D) imaging modality, but the specimen thickness that can be imaged is limited by depth-dependent signal attenuation. Both software and hardware methods have been used to correct the attenuation in reconstructed images, but previous methods do not increase the image signal-to-noise ratio (SNR) using conventional specimen preparation and imaging. We present a practical two-view method that increases the overall imaging depth, corrects signal attenuation and improves the SNR. This is achieved by a combination of slightly modified but conventional specimen preparation, image registration, montage synthesis and signal reconstruction methods. The specimen is mounted in a symmetrical manner between a pair of cover slips, rather than between a slide and a cover slip. It is imaged sequentially from both sides to generate two 3D image stacks from perspectives separated by approximately 180 degrees with respect to the optical axis. An automated image registration algorithm performs a precise 3D alignment, and a model-based minimum mean squared algorithm synthesizes a montage, combining the content of both the 3D views. Experiments with images of individual neurones contrasted with a space-filling fluorescent dye in thick brain tissue slices produced precise 3D montages that are corrected for depth-dependent signal attenuation. The SNR of the reconstructed image is maximized by the method, and it is significantly higher than in the single views after applying our attenuation model. We also compare our method with simpler two-view reconstruction methods and quantify the SNR improvement. The reconstructed images are a more faithful qualitative visualization of the specimen's structure and are quantitatively more accurate, providing a more rigorous basis for automated image analysis.

Animals↗

PubMed2003

Algorithms for accurate 3D registration of neuronal images acquired by confocal scanning laser microscopy.

This paper presents automated and accurate algorithms based on high-order transformation models for registering three-dimensional (3D) confocal images of dye-injected neurons. The algorithms improve upon prior methods in several ways, and meet the more stringent image registration needs of applications such as two-view attenuation correction recently developed by us. First, they achieve high accuracy ( approximately 1.2 voxels, equivalent to 0.4 micro m) by using landmarks, rather than intensity correlations, and by using a high-dimensional affine and quadratic transformation model that accounts for 3D translation, rotation, non-isotropic scaling, modest curvature of field, distortions and mechanical inconsistencies introduced by the imaging system. Second, they use a hierarchy of models and iterative algorithms to eliminate potential instabilities. Third, they incorporate robust statistical methods to achieve accurate registration in the face of inaccurate and missing landmarks. Fourth, they are fully automated, even estimating the initial registration from the extracted landmarks. Finally, they are computationally efficient, taking less than a minute on a 900-MHz Pentium III computer for registering two images roughly 70 MB in size. The registration errors represent a combination of modelling, estimation, discretization and neuron tracing errors. Accurate 3D montaging is described; the algorithms have broader applicability to images of vasculature, and other structures with distinctive point, line and surface landmarks.

Algorithms↗

PubMed2001

Optimal scheduling of tracing computations for real-time vascular landmark extraction from retinal fundus images.

Recently, this group published fast algorithms for automatic tracing (vectorization) of the vasculature in live retinal angiograms, and for the extraction of visual landmarks formed by vascular bifurcations and crossings. These landmarks are used for feature-based image matching for controlling a computer-assisted laser retinal surgery instrument currently under development. This paper describes methods to schedule the vascular tracing computations to maximize the rate of growth of quality of the partial tracing results within a frame cycle. There are two main advantages. First, progressive image matching from partially extracted landmark sets can be faster, and provide an earlier indication of matching failure. Second, the likelihood of successful image matching is greatly improved since the extracted landmarks are of the highest quality for the given computational budget. The scheduling method is based on quantitative measures for the computational work and the quality of landmarks. A coarse grid-based analysis of the image is used to generate seed points for the tracing computations, along with estimates of local edge strengths, orientations, and vessel thickness. These estimates are used to define criteria for real-time preemptive scheduling of the tracing computations. It is shown that the optimal schedule can only be achieved in perfect hindsight, and is thus unrealizable. This leads to scheduling heuristics that approximate the behavior of the optimal algorithm. One such approximation produced approximately 400% improvement in the quality of the partial results at a defined milestone, as compared to random scheduling. The resulting algorithm can be readily implemented on conventional and multiple-processor systems, and is being applied to computer-assisted laser retinal surgery.

Algorithms↗

PubMed1999

Application and Quantitative Validation of Computer-Automated Three-Dimensional Counting of Cell Nuclei.

: This study provides a quantitative validation of qualitative automated three-dimensional (3-D) analysis methods reported earlier. It demonstrates the applicability and quantitative accuracy of our method to detect, characterize, and count Feulgen stained cell nuclei in two tissues (hippocampus and testes). These methods can provide important insights into the interpretation of biological, pharmacological, pathological, and toxicological events. A laser-scanned confocal light microscope was used to record 3-D images in which our algorithms automatically identified individual nuclei from the optical sections given an estimate of minimum nuclear size. The hippocampal data sets were also manually counted independently by five trained observers using the STERECON 3-D image reconstruction system. The automated and manual counts were compared. The computer counts were lower ( approximately 14%) than the manual counts, mainly because the algorithms counted a nucleus only if it was present in five consecutive optical sections but the human counters included nuclei that were in fewer optical sections. A nucleus-by-nucleus comparison of the manual and automated counts verified that the automated analysis was accurate and reproducible, and permitted additional quantitative analyses not available from manual methods. The algorithms also identified subpopulations of nuclei within the hippocampal samples, and haploid and diploid nuclei in the testes. Our methods were shown to be repeatable, accurate, and more consistent than manual counting. Nuclei in regions of high (hippocampal pyramidal layer) and low (extrapyramidal layer) density were distinguished with equal ease. Haploid and diploid nuclei were distinguished in the testes, demonstrating that our automated method may be useful for ploidy analysis. The results presented here on hippocampus and testis are consistent with other qualitative results from the liver and from immunohistochemically labeled substantia nigra, demonstrating the applicability of our software across tissues and preparation methods.

Journal Article↗

PubMed1999

Rapid automated tracing and feature extraction from retinal fundus images using direct exploratory algorithms.

Algorithms are presented for rapid, automatic, robust, adaptive, and accurate tracing of retinal vasculature and analysis of intersections and crossovers. This method improves upon prior work in several ways: 1) automatic adaptation from frame to frame without manual initialization/adjustment, with few tunable parameters; 2) robust operation on image sequences exhibiting natural variability, poor and varying imaging conditions, including over/under-exposure, low contrast, and artifacts such as glare; 3) does not require the vasculature to be connected, so it can handle partial views; and 4) operation is efficient enough for use on unspecialized hardware, and amenable to deadline-driven computing, being able to produce a rapidly and monotonically improving sequence of usable partial results. Increased computation can be traded for superior tracing performance. Its efficiency comes from direct processing on gray-level data without any preprocessing, and from processing only a minimally necessary fraction of pixels in an exploratory manner, avoiding low-level image-wide operations such as thresholding, edge detection, and morphological processing. These properties make the algorithm suited to real-time, on-line (live) processing and is being applied to computer-assisted laser retinal surgery.

Algorithms↗

PubMed1998

Image processing algorithms for retinal montage synthesis, mapping, and real-time location determination.

Although laser retinal surgery is the best available treatment for choridal neovascularization, the current procedure has a low success rate (50%). Challenges, such as motion-compensated beam steering, ensuring complete coverage and minimizing incidental photodamage, can be overcome with improved instrumentation. This paper presents core image processing algorithms for 1) rapid identification of branching and crossover points of the retinal vasculature; 2) automatic montaging of video retinal angiograms; 3) real-time location determination and tracking using a combination of feature-tagged point-matching and dynamic-pixel templates. These algorithms tradeoff conflicting needs for accuracy, robustness to image variations (due to movements and the difficulty of providing steady illumination) and noise, and operational speed in the context of available hardware. The algorithm for locating vasculature landmarks performed robustly at a speed of 16-30 video image frames/s depending upon the field on a Silicon Graphics workstation. The montaging algorithm performed at a speed of 1.6-4 s for merging 5-12 frames. The tracking algorithm was validated by manually locating six landmark points on an image sequence with 180 frames, demonstrating a mean-squared error of 1.35 pixels. It successfully detected and rejected instances when the image dimmed, faded, lost contrast, or lost focus.

Algorithms↗

PubMed1998

Accuracy of nuclear classification in cervical smear images. Quantitative impact of computational deconvolution and 3-D feature computation.

OBJECTIVE: To investigate the accuracy with which the nuclei of cells in overlapped and thick clusters in cervical/ vaginal smears can be classified independent of the segmentation algorithm used and to determine the influence of three-dimensional (3-D) processing as compared to two-dimensional (2-D) methods on classification of the nuclei. STUDY DESIGN: Cell clusters were imaged from 31 ThinPrep smears composed of 808 nuclei, of which 420 were determined to be abnormal by a cytotechnologist. Sets of 2-D and 3-D volumetric features of the detected nuclei were formulated, and classifiers were constructed. The effect of computational deconvolution on classification was assessed using nearest-neighbor and Wiener filter in 2-D and 3-D before calculating features. A "best focus plane" was calculated for each nucleus from the 3-D data set, and the 2-D features in this plane were also analyzed.

Algorithms↗

PubMed1998

Advances in high-speed, three-dimensional imaging and automated segmentation algorithms for thick and overlapped clusters in cytologic preparations. Application to cervical smears.

OBJECTIVE: To use three-dimensional (3-D) imaging and localized adaptive image analysis to enable automated cervical smear screening systems to efficiently and effectively process thick and overlapped cell clusters currently left unprocessed. STUDY DESIGN: Instrumentation was developed to perform high-speed (50-200 optical sections per second at 256 x 256 resolution), 3-D imaging of thick regions of cervical smears. Normal and abnormal ThinPrep smears were imaged at two levels of resolution to approximate higher-resolution, wide-area imaging. Improved dual-resolution, 3-D image analysis algorithms were developed for segmenting nuclei in these clusters. RESULTS: Despite low contrast, high variability and dense overlaps, the algorithms detected 89% and correctly segmented 76% of nuclei in clusters from normal smears and detected 75% and correctly segmented 45% of nuclei in clusters from abnormal smears in low-resolution images. In high-resolution images they detected 88% and segmented 76% of nuclei from normal specimens and detected 55% and segmented 45% of nuclei from abnormal specimens. At least one nucleus from each cell cluster was correctly segmented. CONCLUSION: Selective application of 3-D imaging and 3-D image analysis to thick and overlapped regions can enable a significant fraction (45-89%) of clustered and embedded cells to be accessed by an automated analysis system. These regions are, for the most part, unprocessable by current two-dimensional methods.

Algorithms↗

PubMed1996

Advances in automated 3-D image analyses of cell populations imaged by confocal microscopy.

Automated three-dimensional (3-D) image analysis methods are presented for rapid and effective analysis of populations of fluorescently labeled cells or nuclei in thick tissue sections that have been imaged three dimensionally using a confocal microscope. The methods presented here greatly improve upon our earlier work (Roysam et al.:J Microsc 173: 115-126, 1994). The principal advances reported are: algorithms for efficient data pre-processing and adaptive segmentation, effective handling of image anisotrophy, and fast 3-D morphological algorithms for separating overlapping or connected clusters utilizing image gradient information whenever available. A particular feature of this method is its ability to separate densely packed and connected clusters of cell nuclei. Some of the challenges overcome in this work include the efficient and effective handling of imaging noise, anisotrophy, and large variations in image parameters such as intensity, object size, and shape. The method is able to handle significant inter-cell, intra-cell, inter-image, and intra-image variations. Studies indicate that this method is rapid, robust, and adaptable. Examples were presented to illustrate the applicability of this approach to analyzing images of nuclei from densely packed regions in thick sections of rat liver, and brain that were labeled with a fluorescent Schiff reagent.

Algorithms↗

PubMed1996

Automated 3-D montage synthesis from laser-scanning confocal images: application to quantitative tissue-level cytological analysis.

This paper presents a landmark based method for efficient, robust, and automated computational synthesis of high-resolution, two-dimensional (2-D) or three-dimensional (3-D) wide-area images of a specimen from a series of overlapping partial views. The synthesized image is the set union of the areas or volumes covered by the partial views, and is called the "montage." This technique is used not only to produce gray-level montages, but also to montage the results of automated image analysis, such as 3-D cell segmentation and counting, so as to generate large representations that are equivalent to processing the large wide-area image at high resolution. The method is based on computing a concise set of feature-tagged landmarks in each partial view, and establishing correspondences between the landmarks using a combinatorial point matching algorithm. This algorithm yields a spatial transformation linking the partial views that can be used to create the montage. Such processing can be a first step towards high-resolution large-scale quantitative tissue studies. A detailed example using 3-D laser-scanning confocal microscope images of acriflavine-stained hippocampal sections of rat brain is presented to illustrate the method.

Animals↗

PubMed1994

Three-dimensional imaging and image analysis of hippocampal neurons: confocal and digitally enhanced wide field microscopy.

The microscopy of biological specimens has traditionally been a two-dimensional imaging method for analyzing what are in reality three-dimensional (3-D) objects. This has been a major limitation of the application of one of science's most widely used tools. Nowhere has this limitation been more acute than in neurobiology, which is dominated by the necessity of understanding both large- and small-scale 3-D anatomy. Fortunately, recent advances in optical instrumentation and computational methods have provided the means for retrieving the third dimension, making full 3-D microscopic imaging possible. Optical designs have concentrated on the confocal imaging mode while computational methods have made 3-D imaging possible with wide field microscopes using deconvolution methods. This work presents a brief review of these methods, especially as applied to neurobiology, and data using both approaches. Specimens several hundred micrometers thick can be sampled allowing essentially intact neurons to be imaged. These neurons or selected components can be contrasted with either fluorescent, absorption, or reflection stains. Image analysis in 3-D is as important as visualization in 3-D. Automated methods of cell counting and analysis by nuclear detection as well as tracing of individual neurons are presented.

Animals↗

PubMed1994

Automated tracing and volume measurements of neurons from 3-D confocal fluorescence microscopy data.

Three-dimensional (3-D) image analysis algorithms and experimental results that demonstrate the feasibility of fully automated tracing of neurons from fluorescence confocal microscopy data are presented. The input to the automated analysis is a set of successive optical slices that have been acquired using a confocal scanning laser microscope. The output of the system is a labelled graph representation of the neuronal topology that is spatially aligned with the 3-D image data. A variety of topological and metric analyses can be carried out using this representation. For instance, precise measurements of volumes, lengths, diameters and tortuosities can be made over specific portions of the neuron that are specified in terms of the graph representation. The effectiveness of the method is demonstrated for a set of sample fields featuring selectively stained neurons. Additional work will be needed to refine the method for unsupervised use with complex data involving multiple intertwined neurons and extremely fine dendritic structures.

Algorithms↗

PubMed1994

Algorithms for automated characterization of cell populations in thick specimens from 3-D confocal fluorescence microscopy data.

Methods are presented for the automated, quantitative and three-dimensional (3-D) analysis of cell populations in thick, essentially intact tissue sections while maintaining intercell spatial relationships. This analysis replaces current manual methods which are tedious and subjective. The thick sample is imaged in three dimensions using a confocal scanning laser microscope. The stack of optical slices is processed by a 3-D segmentation algorithm that separates touching and overlapping structures using localization constraints. Adaptive data reduction is used to achieve computational efficiency. A hierarchical cluster analysis algorithm is used automatically to characterize the cell population by a variety of cell features. It allows automatic detection and characterization of patterns such as the 3-D spatial clustering of cells, and the relative distributions of cells of various sizes. It also permits the detection of structures that are much smaller, larger, brighter, darker, or differently shaped than the rest of the population. The overall method is demonstrated for a set of rat brain tissue sections that were labelled for tyrosine hydroxylase using fluorescein-conjugated antibodies. The automated system was verified by comparison with computer-assisted manual counts from the same image fields.

Algorithms↗

PubMed1993

Developments in three-dimensional stereo brightfield microscopy.

We present recent developments of a widefield computer/microscope system and image reconstruction algorithm for producing three-dimensional (3D) increased depth of field images in the form of brightfield stereo pairs of thick specimens. The theoretical principle of this image reconstruction technique is based on Weiner-type inverse filtering. A number of extensions and refinements to our previous work have included further testing of the system with a broader class of specimens and the implementation of several pragmatic refinements important for future 3D microscopy systems. These refinements include histogram modification routines for improving visualization, a preprocessing routine to eliminate edge artifacts due to circular convolution and other effects, stereo viewing angle optimization, a rule of thumb estimate for the axial sampling rate, and incorporation of a variation of the Fast Fourier Transform and filtering operations that significantly reduce computational time. Images of spyrogyra, neonatal rat hippocampal neurons, and cervical/vaginal cell smears are presented to show the utility of these methods for 3D visualization. The primary advantages of these methods are that they operate with an ordinary transmitted light microscope and are inexpensively implemented on a personal computer with reasonable computation time.

Algorithms↗

PubMed1993

Iterative, constrained 3-D image reconstruction of transmitted light bright-field micrographs based on maximum likelihood estimation.

We present several image reconstruction algorithms for generating three-dimensional (3-D) renderings of bright-field micrographs that are founded on maximum likelihood estimation (MLE) theory. The basic principle of the algorithms is in estimating the values of the optical densities of the specimen. A computer simulation and initial experimental testing of a steepest ascent version of the algorithm is presented. The computer simulation demonstrates that the MLE algorithm has an advantage over previously used inverse filtering techniques in that it partially restores the zeroed Fourier components in the well-known missing-cone region. We present 3-D reconstructions from real biological data to show the potential of the algorithm in practical applications.

Algorithms↗