973 resultados para Optical images.


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The cellular rheology has recently undergone a rapid development with particular attention to the cytoskeleton mechanical properties and its main components - actin filaments, intermediate filaments, microtubules and crosslinked proteins. However it is not clear what are the cellular structural changes that directly affect the cell mechanical properties. Thus, in this work, we aimed to quantify the structural rearrangement of these fibers that may emerge in changes in the cell mechanics. We created an image analysis platform to study smooth muscle cells from different arteries: aorta, mammary, renal, carotid and coronary and processed respectively 31, 29, 31, 30 and 35 cell image obtained by confocal microscopy. The platform was developed in Matlab (MathWorks) and it uses the Sobel operator to determine the actin fiber image orientation of the cell, labeled with phalloidin. The Sobel operator is used as a filter capable of calculating the pixel brightness gradient, point to point, in the image. The operator uses vertical and horizontal convolution kernels to calculate the magnitude and the angle of the pixel intensity gradient. The image analysis followed the sequence: (1) opens a given cells image set to be processed; (2) sets a fix threshold to eliminate noise, based on Otsu's method; (3) detect the fiber edges in the image using the Sobel operator; and (4) quantify the actin fiber orientation. Our first result is the probability distribution II(Δθ) to find a given fiber angle deviation (Δθ) from the main cell fiber orientation θ0. The II(Δθ) follows an exponential decay II(Δθ) = Aexp(-αΔθ) regarding to its θ0. We defined and determined a misalignment index α of the fibers of each artery kind: coronary αCo = (1.72 ‘+ or =’ 0.36)rad POT -1; renal αRe = (1.43 + or - 0.64)rad POT -1; aorta αAo = (1.42 + or - 0.43)rad POT -1; mammary αMa = (1.12 + or - 0.50)rad POT -1; and carotid αCa = (1.01 + or - 0.39)rad POT -1. The α of coronary and carotid are statistically different (p < 0.05) among all analyzed cells. We discussed our results correlating the misalignment index data with the experimental cell mechanical properties obtained by using Optical Magnetic Twisting Cytometry with the same group of cells.

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Over the last few years, low-level light therapy (LLLT) has shown an incredible suitability for a wide range of applications for central nervous system (CNS) related diseases. In this therapeutic modality light dosimetry is extremely critical so the study of light propagation through the CNS organs is of great importance. To better understand how light intensity is delivered to the most relevant neural sites we evaluated optical transmission through slices of rat brain point by point. We experimented red (λ = 660 nm) and near infrared (λ = 808 nm) diode laser light analyzing the light penetration and distribution in the whole brain. A fresh Wistar rat (Rattus novergicus) brain was cut in sagittal slices and illuminated with a broad light beam. A high-resolution digital camera was employed to acquire data of transmitted light. Spatial profiles of the light transmitted through the sample were obtained from the images. Peaks and valleys in the profiles show sites where light was less or more attenuated. The peak intensities provide information about total attenuation and the peak widths are correlated to the scattering coefficient at that individual portion of the sample. The outcomes of this study provide remarkable information for LLLT dose-dependent studies involving CNS and highlight the importance of LLLT dosimetry in CNS organs for large range of applications in animal and human diseases.

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The measurement of mesozooplankton biomass in the ocean requires the use of analytical procedures that destroy the samples. Alternatively, the development of methods to estimate biomass from optical systems and appropriate conversion factors could be a compromise between the accuracy of analytical methods and the need to preserve the samples for further taxonomic studies. The conversion of the body area recorded by an optical counter or a camera, by converting the digitized area of an organism into individual biomass, was suggested as a suitable method to estimate total biomass. In this study, crustacean mesozooplankton from subtropical waters were analyzed, and individual dry weight and body area were compared. The obtained relationships agreed with other measurements of biomass obtained from a previous study in Antarctic waters. Gelatinous mesozooplankton from subtropical and Antarctic waters were also sampled and processed for body area and biomass. As expected, differences between crustacean and gelatinous plankton were highly significant. Transparent gelatinous organisms have a lower dry weight per unit area. Therefore, to estimate biomass from digitized images, pattern recognition discerning, at least, between crustaceans and gelatinous forms is required.

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[EN] We propose four algorithms for computing the inverse optical flow between two images. We assume that the forward optical flow has already been obtained and we need to estimate the flow in the backward direction. The forward and backward flows can be related through a warping formula, which allows us to propose very efficient algorithms. These are presented in increasing order of complexity. The proposed methods provide high accuracy with low memory requirements and low running times.In general, the processing reduces to one or two image passes. Typically, when objects move in a sequence, some regions may appear or disappear. Finding the inverse flows in these situations is difficult and, in some cases, it is not possible to obtain a correct solution. Our algorithms deal with occlusions very easy and reliably. On the other hand, disocclusions have to be overcome as a post-processing step. We propose three approaches for filling disocclusions. In the experimental results, we use standard synthetic sequences to study the performance of the proposed methods, and show that they yield very accurate solutions. We also analyze the performance of the filling strategies. 

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[EN] The seminal work of Horn and Schunck [8] is the first variational method for optical flow estimation. It introduced a novel framework where the optical flow is computed as the solution of a minimization problem. From the assumption that pixel intensities do not change over time, the optical flow constraint equation is derived. This equation relates the optical flow with the derivatives of the image. There are infinitely many vector fields that satisfy the optical flow constraint, thus the problem is ill-posed. To overcome this problem, Horn and Schunck introduced an additional regularity condition that restricts the possible solutions. Their method minimizes both the optical flow constraint and the magnitude of the variations of the flow field, producing smooth vector fields. One of the limitations of this method is that, typically, it can only estimate small motions. In the presence of large displacements, this method fails when the gradient of the image is not smooth enough. In this work, we describe an implementation of the original Horn and Schunck method and also introduce a multi-scale strategy in order to deal with larger displacements. For this multi-scale strategy, we create a pyramidal structure of downsampled images and change the optical flow constraint equation with a nonlinear formulation. In order to tackle this nonlinear formula, we linearize it and solve the method iteratively in each scale. In this sense, there are two common approaches: one that computes the motion increment in the iterations, like in ; or the one we follow, that computes the full flow during the iterations, like in. The solutions are incrementally refined ower the scales. This pyramidal structure is a standard tool in many optical flow methods.

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[EN] The aim of this work is to propose a model for computing the optical flow in a sequence of images. We introduce a new temporal regularizer that is suitable for large displacements. We propose to decouple the spatial and temporal regularizations to avoid an incongruous formulation. For the spatial regularization we use the Nagel-Enkelmann operator and a newly designed temporal regularization. Our model is based on an energy functional that yields a partial differential equation (PDE). This PDE is embedded into a multipyramidal strategy to recover large displacements. A gradient descent technique is applied at each scale to reach the minimum.

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[EN] In this paper we show that a classic optical flow technique by Nagel and Enkelmann can be regarded as an early anisotropic diffusion method with a diffusion tensor. We introduce three improvements into the model formulation that avoid inconsistencies caused by centering the brightness term and the smoothness term in different images use a linear scale-space focusing strategy from coarse to fine scales for avoiding convergence to physically irrelevant local minima, and create an energy functional that is invariant under linear brightness changes.  Applying a gradient descent method to the resulting energy functional leads to a system of diffusion-reaction equations. We prove that this system has a unique solution under realistic assumptions on the initial data, and we present an efficient linear implicit numerical scheme in detail. Our method creates flow fields with 100% density over the entire image domain, it is robust under a large range of parameter variations, and it can recover displacement fields that are far beyond the typical one-pixel limits which are characteristic for many differential methods for determining optical flow. We show that it performs better than the classic optical flow methods with 100%  density that are evaluated by Barron et al. (1994). Our software is available from the Internet.

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Satellite remote sensing has proved to be an effective support in timely detection and monitoring of marine oil pollution, mainly due to illegal ship discharges. In this context, we have developed a new methodology and technique for optical oil spill detection, which make use of MODIS L2 and MERIS L1B satellite top of atmosphere (TOA) reflectance imagery, for the first time in a highly automated way. The main idea was combining wide swaths and short revisit times of optical sensors with SAR observations, generally used in oil spill monitoring. This arises from the necessity to overcome the SAR reduced coverage and long revisit time of the monitoring area. This can be done now, given the MODIS and MERIS higher spatial resolution with respect to older sensors (250-300 m vs. 1 km), which consents the identification of smaller spills deriving from illicit discharge at sea. The procedure to obtain identifiable spills in optical reflectance images involves removal of oceanic and atmospheric natural variability, in order to enhance oil-water contrast; image clustering, which purpose is to segment the oil spill eventually presents in the image; finally, the application of a set of criteria for the elimination of those features which look like spills (look-alikes). The final result is a classification of oil spill candidate regions by means of a score based on the above criteria.

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Percutaneous needle intervention based on PET/CT images is effective, but exposes the patient to unnecessary radiation due to the increased number of CT scans required. Computer assisted intervention can reduce the number of scans, but requires handling, matching and visualization of two different datasets. While one dataset is used for target definition according to metabolism, the other is used for instrument guidance according to anatomical structures. No navigation systems capable of handling such data and performing PET/CT image-based procedures while following clinically approved protocols for oncologic percutaneous interventions are available. The need for such systems is emphasized in scenarios where the target can be located in different types of tissue such as bone and soft tissue. These two tissues require different clinical protocols for puncturing and may therefore give rise to different problems during the navigated intervention. Studies comparing the performance of navigated needle interventions targeting lesions located in these two types of tissue are not often found in the literature. Hence, this paper presents an optical navigation system for percutaneous needle interventions based on PET/CT images. The system provides viewers for guiding the physician to the target with real-time visualization of PET/CT datasets, and is able to handle targets located in both bone and soft tissue. The navigation system and the required clinical workflow were designed taking into consideration clinical protocols and requirements, and the system is thus operable by a single person, even during transition to the sterile phase. Both the system and the workflow were evaluated in an initial set of experiments simulating 41 lesions (23 located in bone tissue and 18 in soft tissue) in swine cadavers. We also measured and decomposed the overall system error into distinct error sources, which allowed for the identification of particularities involved in the process as well as highlighting the differences between bone and soft tissue punctures. An overall average error of 4.23 mm and 3.07 mm for bone and soft tissue punctures, respectively, demonstrated the feasibility of using this system for such interventions. The proposed system workflow was shown to be effective in separating the preparation from the sterile phase, as well as in keeping the system manageable by a single operator. Among the distinct sources of error, the user error based on the system accuracy (defined as the distance from the planned target to the actual needle tip) appeared to be the most significant. Bone punctures showed higher user error, whereas soft tissue punctures showed higher tissue deformation error.

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The purpose of this study was to compare inter-observer agreement of Stratus™ OCT versus Spectralis™ OCT image grading in patients with neovascular age-related macular degeneration (AMD). Thirty eyes with neovascular AMD were examined with Stratus™ OCT and Spectralis™ OCT. Four different scan protocols were used for imaging. Three observers graded the images for the presence of various pathologies. Inter-observer agreement between OCT models was assessed by calculating intra-class correlation coefficients (ICC). In Stratus™ OCT highest interobserver agreement was found for subretinal fluid (ICC: 0.79), and in Spectralis™ OCT for intraretinal cysts (IRC) (ICC: 0.93). Spectralis™ OCT showed superior interobserver agreement for IRC and epiretinal membranes (ERM) (ICC(Stratus™): for IRC 0.61; for ERM 0.56; ICC(Spectralis™): for IRC 0.93; for ERM 0.84). Increased image resolution of Spectralis™ OCT did improve the inter-observer agreement for grading intraretinal cysts and epiretinal membranes but not for other retinal changes.

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BACKGROUND: In this paper, we present a new method for the calibration of a microscope and its registration using an active optical tracker. METHODS: Practically, both operations are done simultaneously by moving an active optical marker within the field of view of the two devices. The IR LEDs composing the marker are first segmented from the microscope images. By knowing their corresponding three-dimensional (3D) position in the optical tracker reference system, it is possible to find the transformation matrix between the referential of the two devices. Registration and calibration parameters can be extracted directly from that transformation. In addition, since the zoom and focus can be modified by the surgeon during the operation, we propose a spline based method to update the camera model to the new setup. RESULTS: The proposed technique is currently being used in an augmented reality system for image-guided surgery in the fields of ear, nose and throat (ENT) and craniomaxillofacial surgeries. CONCLUSIONS: The results have proved to be accurate and the technique is a fast, dynamic and reliable way to calibrate and register the two devices in an OR environment.

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To analyze the impact of opacities in the optical pathway and image compression of 32-bit raw data to 8-bit jpg images on quantified optical coherence tomography (OCT) image analysis.

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PURPOSE: To correlate the dimension of the visual field (VF) tested by Goldman kinetic perimetry with the extent of visibility of the highly reflective layer between inner and outer segments of photoreceptors (IOS) seen in optical coherence tomography (OCT) images in patients with retinitis pigmentosa (RP). METHODS: In a retrospectively designed cross-sectional study, 18 eyes of 18 patients with RP were examined with OCT and Goldmann perimetry using test target I4e and compared with 18 eyes of 18 control subjects. A-scans of raw scan data of Stratus OCT images (Carl Zeiss Meditec, AG, Oberkochen, Germany) were quantitatively analyzed for the presence of the signal generated by the highly reflective layer between the IOS in OCT images. Starting in the fovea, the distance to which this signal was detectable was measured. Visual fields were analyzed by measuring the distance from the center point to isopter I4e. OCT and visual field data were analyzed in a clockwise fashion every 30 degrees , and corresponding measures were correlated. RESULTS: In corresponding alignments, the distance from the center point to isopter I4e and the distance to which the highly reflective signal from the IOS can be detected correlate significantly (r = 0.75, P < 0.0001). The greater the distance in VF, the greater the distance measured in OCT. CONCLUSIONS: The authors hypothesize that the retinal structure from which the highly reflective layer between the IOS emanates is of critical importance for visual and photoreceptor function. Further research is warranted to determine whether this may be useful as an objective marker of progression of retinal degeneration in patients with RP.

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BACKGROUND/AIM: To compare the ability of confocal scanning laser tomography (CSLT), scanning laser polarimetry (SLP) and optical coherence tomography (OCT) in recognising localised retinal nerve fibre layer (RNFL) defects. METHODS: 51 eyes from 43 patients with glaucoma were identified by two observers as having RNFL defects visible on optic disc photographs. 51 eyes of 32 normal subjects were used as controls. Three masked observers evaluated CSLT, SLP and OCT images to determine subjectively the presence of localised RNFL defects. RESULTS: Interobserver agreement was highest with OCT, followed by SLP and CSLT (mean kappa: 0.83, 0.69 and 0.64, respectively). RNFL defects were identified in 58.8% of CSLT, 66.7% of SLP and 54.9% of OCT (p = 0.02 between SLP and OCT) by at least two observers. In the controls, 94.1% of CSLT, 84.3% of SLP and 94.1% of OCT scans, respectively, were rated as normal (p = 0.02 between CSLT and SLP, and SLP and OCT). CONCLUSION: Approximately 20-40% of localised RNFL defects identified by colour optic disc photographs are not detected by CSLT, SPL or OCT. SLP showed a higher number of false-positive results than the other techniques, but also had a higher proportion of correctly identified RNFL defects in the glaucoma population.