Changes In Image Intensity Research Articles

Changes in intervertebral disc morphology persist 5 mo after 21-day bed rest

As part of the nutrition-countermeasures (NUC) study in Cologne, Germany in 2010, seven healthy male subjects underwent 21 days of head-down tilt bed rest and returned 153 days later to undergo a second bout of 21-day bed rest. As part of this model, we aimed to examine the recovery of the lumbar intervertebral discs and muscle cross-sectional area (CSA) after bed rest using magnetic resonance imaging and conduct a pilot study on the effects of bed rest in lumbar muscle activation, as measured by signal intensity changes in T(2)-weighted images after a standardized isometric spinal extension loading task. The changes in intervertebral disc volume, anterior and posterior disc height, and intervertebral length seen after bed rest did not return to prebed-rest values 153 days later. While recovery of muscle CSA occurred after bed rest, increases (P ≤ 0.016) in multifidus, psoas, and quadratus lumborum muscle CSA were seen 153 days after bed rest. A trend was seen for greater activation of the erector spinae and multifidus muscles in the standardized loading task after bed rest. Greater reductions of multifidus and psoas CSA muscle and greater increases in multifidus signal intensity with loading were associated with incidence of low back pain in the first 28 days after bed rest (P ≤ 0.044). The current study contributes to our understanding of the recovery of the lumbar spine after 21-day bed rest, and the main finding was that a decrease in spinal extensor muscle CSA recovers within 5 mo after bed rest but that changes in the intervertebral discs persist.

SU‐E‐T‐452: Dynamic Intensity Modulator

Purpose: To reduce the radiotherapy treatment time per freaction in order to decrease the possibility of patient movement during treatment and increase patient comfort. Methods: A prototype of a Dynamic Intensity Modulator (DIM) was created which changes fluence profiles dynamically and autonomously between treatment grantry angles. Radiation Absorbing Material (RAM) is dynamically displaced in and out of the radiation beam path by radio‐translucent columns. A reservoir regulates the amount of RAM in the beam path. Between gantry angles columns shift to create new fluence profiles. Measurements of beam fluence were acquired using portal images for various RAM thicknesses. Results: Imaging varying RAM thicknesses shows definite changes in image intensity. Initially the columns were at the zero position, so a constant height layer of RAM was achieved. By comparing a constant height layer of RAM against a thicker constant height layer of RAM, an increase in attenuation was observed. Different columns height configurations were also tested. Again, areas with a thicker layer of RAM had a higher level of attenuation than areas with a thinner layer of RAM. In all tests the prototype columns used to set the height of RAM were visible. This will be resolved by creating columns, which are more radio‐translucent. Also, a significant amount of noise was visible in the attenuation profiles. This was most likely due to the material choice of RAM, a homogenous mixture of 2 different diameter lead BBˈs. Conclusions: Despite the non‐uniformity within intensity profiles, this study demonstrates the fundamental concept of the DIM. The prototype was able to displace deformable RAM in different locations to create distinct fluence profiles.

Quantification of fibre polymerization through Fourier space image analysis.

Quantification of changes in the total length of randomly oriented and possibly curved lines appearing in an image is a necessity in a wide variety of biological applications. Here, we present an automated approach based upon Fourier space analysis. Scaled, band-pass filtered power spectral densities of greyscale images are integrated to provide a quantitative measurement of the total length of lines of a particular range of thicknesses appearing in an image. A procedure is presented to correct for changes in image intensity. The method is most accurate for two-dimensional processes with fibres that do not occlude one another.

Cyclic CINE‐balanced steady‐state free precession image intensity variations: Implications for the detection of myocardial edema

To evaluate the dependence of CINE-balanced steady-state free precession (bSSFP) image intensities on spatial location, cardiac phase, and disease state. Eight subjects with recent myocardial infarctions and eight age- and sex-matched normal volunteers were studied using CINE-bSSFP imaging to describe cyclic image intensity variations as a function of the cardiac cycle and to optimize and assess the ability of CINE-bSSFP imaging to depict myocardial edema. Signal intensities of the left ventricular (LV) bloodpool and myocardium were measured using region-of-interest analysis across the cardiac cycle. The magnitude and time course of the cyclic variations were evaluated. Mixed-model analysis of variance was used to examine the influence of physical location, cardiac phase, and presence of myocardial infarction. The LV bloodpool and myocardial CINE-bSSFP signal intensities varied significantly with spatial location, cardiac phase, and disease (P < 0.001). Cardiac phase had a significant effect on the signal intensities after adjustments for spatial location. The LV bloodpool signal decreased slowly during systole and rose sharply during LV filling. There were two distinct myocardial intensity peaks, one occurring at peak systole and the other at the end of the LV rapid inflow phase. Myocardial edema was seen as a hyperintense region. Image contrast with adjacent myocardium was the greatest at the end of systole. Detection of myocardial edema using the conventional CINE-bSSFP technique is feasible, but is complicated by normal cyclic changes in myocardial image intensities during the cardiac cycle.

Micro-magnetic resonance imaging study of live quail embryos during embryonic development

Eggs containing live Japanese quail embryos were imaged using micro-magnetic resonance imaging (μMRI) at 24-h intervals from Day 0 to 8, the period during which the main body axis is being laid down and organogenesis is taking place. Considerable detail of non-embryonic structures such as the latebra was revealed at early stages but the embryo could only be visualized around Day 3. Three-dimensional (3D) changes in embryo length and volume were quantified and also changes in volume in the extra- and non-embryonic components. The embryo increased in length by 43% and nearly trebled in volume between Day 4 and Day 5. Although the amount of yolk remained fairly constant over the first 5 days, the amount of albumen decreases significantly and was replaced by extra-embryonic fluid (EEF). 1H longitudinal (T1) and transverse (T2) relaxation times of different regions within the eggs were determined over the first 6 days of development. The T2 measurements mirrored the changes in image intensity observed, which can be related to the aqueous protein concentrations. In addition, a comparison of the development of Day 0 to 3 quail embryos exposed to radiofrequency (rf) pulses, 7 T static magnetic fields and magnetic field gradients for an average of 7 h with the development of control embryos did not reveal any gross changes, thus confirming that μMRI is a suitable tool for following the development of live avian embryos over time from the earliest stages.

Quantification of carbon contamination under electron beam irradiation in a scanning transmission electron microscope and its suppression by plasma cleaning

We have measured the build-up of carbon surface contamination as a function of time and irradiated area size for various specimens in a JEOL 2010F (scanning) transmission electron microscope, employing both t/λ mapping with our Gatan imaging filter and recording changes in annular dark-field image intensity. It is shown that the total number of carbon atoms deposited per time for a given beam intensity is roughly constant at room temperature for as-received specimens while it is significantly lower for plasma cleaned specimens. This explains why contamination is generally only an issue at the highest magnifications where the contamination regions become smaller and the carbon layers correspondingly thicker. A Fischione plasma cleaner was then used to remove these carbon layers, and the rate of carbon removal has been determined for contamination spots produced in stationary spot mode as well as for extended regions scanned for a minute so that optimal cleaning times can be chosen.

A Modified PSO Algorithm for Remote Sensing Image Template Matching

Image template matching is essential in image analysis and computer vision tasks. Cross-correlation algorithms are often used in practice, but they are sensitive to nonlinear changes in image intensity and random noise, and are computationally expensive. In this paper, we propose a template-matching algorithm based on a modified particle swarm optimization (PSO) procedure with a mutual information (MI) similarity measure. The influence of MI on the performance of template matching, calculated by different histogram bins, is analyzed first. A modified PSO method (CRI-PSO) is then presented. The proposed algorithm is tested with remote sensing imagery from different sensors and for different seasons. Our experimental results indicate that the proposed approach is robust in practical scenarios and outperforms the standard PSO , multi-start PSO , and cross-correlation algorithms in accuracy and efficiency with our test data. The proposed method can be used for position estimation of aircraft, object recognition, and image retrieval.

Analysis of colour channel coupling from a physics-based viewpoint: Application to colour edge detection

The Dichromatic Reflection Model (DRM) introduced by Shafer in 1985 is surely the most referenced physics-based model of image formation. A preliminary analysis of this model derives in the conclusion that colour channels remain coupled by the reflectance of objects surface material. Taking this observation as a basis, this paper shows that this coupling manifests itself at the signal level in the form of a set of properties only satisfied in uniform reflectance areas. Such properties are deeply analysed and formalized throughout the paper, and, eventually, they are stated geometrically. As will be seen, a compatibility relationship stems from this geometric interpretation, which allows checking at a very low cost whether two pixels correspond to the same scene reflectance or not. Finally, an edge detector based on the use of the previous relationship is presented as an example of application. This edge detector inherits all the properties of the compatibility relationship: simplicity, low computational power requirements, sensor noise adaptivity and insensitivity to image intensity changes due to scene objects curvature.

Autonomous sub-image matching for two-dimensional electrophoresis gels using MaxRST algorithm

Matching two-dimensional electrophoresis (2-DE) gel images typically generates a bottleneck in the automated protein analysis, and image distortion and experimental variation, which reduce the matching accuracy. However, conventional matching schemes only compare two complete images, and landmark selection and registration procedures are rather time-consuming. This work presents a novel and robust Maximum Relation Spanning Tree (MaxRST) algorithm, in which an autonomous sub-image matching method does not require registering or manual selection of landmarks. The 2D gel images are represented graphically. Image features are then quantitatively extracted regardless of image size. Similarity between a sub-image and large image is then determined based on Gaussian similarity measurement inspired by fuzzy method, thereby increasing the accuracy of fractional matching. The proposed autonomous matching algorithm achieves an accuracy of up to 97.29% when matching 627 2-DE gel test images. In addition to accommodating image rotation, reversals, shape deformation and intensity changes, the proposed algorithm effectively addresses the sub-image mapping problem and was analyzed thoroughly using a large dataset containing 4629 images. The contributions of this work are twofold. First, this work presents a novel MaxRST strategy and autonomous matching method that does not require manual landmark selection. Second, the proposed method, which extends 2-DE gel matching to query sub-image and a database containing large sets of images, can be adopted for mapping and locating, and to compare small gel images with large gel images with robustness and efficiency.

Variation in Epidermal Morphology in Human Skin at Different Body Sites as Measured by Reflectance Confocal Microscopy

Two methods of estimating stratum corneum thickness using reflectance confocal microscopy were examined, and epidermal thickness measurements at multiple body sites were compared. Measurements of stratum corneum thickness were made using the derivative method, which is based on the rate of change of image intensity as a proxy for keratin concentration, and simple visual analysis of confocal images. To compare epidermal thickness we collected 1491 z-axis stacks of confocal images from 10 body sites in 39 subjects. An artefact associated with the imaging process interfered with the derivative method for stratum corneum thickness, and simple visual analysis is to be preferred. Although some epidermal properties varied by site, the most striking finding was the degree of within-site variation, which accounted for between 50% and 74% of the total variation observed. The majority of this variation was not due to measurement error, and represents genuine topographical irregularity. This fine-scale variation limits the ease of use of reflectance confocal microscopy for quantitative studies of the epidermis and stratum corneum.

Image Ratio Features for Facial Expression Recognition Application

Video-based facial expression recognition is a challenging problem in computer vision and human-computer interaction. To target this problem, texture features have been extracted and widely used, because they can capture image intensity changes raised by skin deformation. However, existing texture features encounter problems with albedo and lighting variations. To solve both problems, we propose a new texture feature called image ratio features. Compared with previously proposed texture features, e.g., high gradient component features, image ratio features are more robust to albedo and lighting variations. In addition, to further improve facial expression recognition accuracy based on image ratio features, we combine image ratio features with facial animation parameters (FAPs), which describe the geometric motions of facial feature points. The performance evaluation is based on the Carnegie Mellon University Cohn-Kanade database, our own database, and the Japanese Female Facial Expression database. Experimental results show that the proposed image ratio feature is more robust to albedo and lighting variations, and the combination of image ratio features and FAPs outperforms each feature alone. In addition, we study asymmetric facial expressions based on our own facial expression database and demonstrate the superior performance of our combined expression recognition system.

Best linear unbiased axial localization in three-dimensional fluorescent bead tracking with subnanometer resolution using off-focus images

A three-dimensional particle tracking technique, based on microscope off-focus images, was introduced in Z. Zhang and C.-H. Menq, Appl. Opt.47, 2361 (2008) and applied to bright-field imaging. This paper presents two major improvements to the axial localization algorithm of the 3D particle tracking technique. First, it extends the algorithm to measure fluorescent particles in the presence of photobleaching and excitation variation. Second, it enhances the measurement resolution by achieving the best linear unbiased estimation of the particle's axial position. Similarly to the original algorithm, a radius vector is first converted from the off-focus 2D image of the particle, and the axial position is estimated by comparing the radius vector with an object-specific model, calibrated automatically prior to each experiment. Although it was an intensity-based method, by normalizing the radius vectors the improved algorithm becomes a shape-based method, thus invariant to image intensity change and robust to photobleaching. Moreover, when considering the noise variance of each point in the radius vector and their correlations, the best linear unbiased estimation based on a linearized model is achieved. It is shown that variance equalization and correlation-weighted optimization greatly reduce the estimation variance and lead to near-uniform localization resolution over the entire measurement range. Estimation resolution is theoretically analyzed and validated by experiments. Theoretical analysis enables the prediction of measurement resolution based on calibration data. Finally, experimental results are presented to illustrate the performance of the measurement method in terms of measurement precision and range, as well as its robustness to intensity variation.

SSFSE sequence functional MRI of the human cervical spinal cord with complex finger tapping

Purpose Functional MR imaging of the human cervical spinal cord was carried out on volunteers during alternated rest and a complex finger tapping task, in order to detect image intensity changes arising from neuronal activity. Methods Functional MR imaging data using single-shot fast spin-echo sequence (SSFSE) with echo time 42.4 ms on a 1.5 T GE Clinical System were acquired in eight subjects performing a complex finger tapping task. Cervical spinal cord activation was measured both in the sagittal and transverse imaging planes. Postprocessing was performed by AFNI (Analysis of Functional Neuroimages) software system. Results Intensity changes (5.5–7.6%) were correlated with the time course of stimulation and were consistently detected in both sagittal and transverse imaging planes of the cervical spinal cord. The activated regions localized to the ipsilateral side of the spinal cord in agreement with the neural anatomy. Conclusion Functional MR imaging signals can be reliably detected with finger tapping activity in the human cervical spinal cord using a SSFSE sequence with 42.4 ms echo time. The anatomic location of neural activity correlates with the muscles used in the finger tapping task.

Determination of painful vertebrae treated by kyphoplasty in multiple-level vertebral compression fractures

To explore how to determine painful vertebrae treated by kyphoplasty in multiple-level osteoporotic vertebral compression fractures and clinical outcome. From October 2002 to June 2005, 51 consecutive procedures with kyphoplasty were performed on 35 patients with multiple-level osteoporotic vertebral compression fractures. There were 51 painful vertebrae among 120 vertebral compression fractures. The painful vertebra was determined by the signal intensity changes in MR images, combined with radiography and local percussion pain before operation. Only painful vertebrae were treated by kyphoplasty. Preoperative, postoperative and final follow-up visual analog scale (VAS) and radiographic findings such as vertebral height and Cobb angle were recorded and analyzed. All patients tolerated the procedure well with immediate relief of their back pain after kyphoplasty and they can walk at 1-3 days after the procedure. There were 3 vertebrae (3/51) occurred asymptomatic extravasation of cement. 31 cases were followed up for mean 16.2 months (range 6-44 months). VAS reduced from preoperative 8.7 to final follow-up 2.1 (P <0. 01). At final follow-up the vertebral height had a recovery rate of 59.17%, and the mean Cobb angle was improved 10.1 degrees. There was a significant improvement between preoperative and final follow-up values (P < 0.01). The painful vertebra can be determined by signal intensity changes in MR series images in multiple-level osteoporotic vertebral compression fractures. Selecting painful vertebrae to be treated by kyphoplasty can make patients with multiple-level VCFs gain an excellent result.

Evaluating an optical-flow-based registration algorithm for contrast-enhanced magnetic resonance imaging of the breast

Dynamic contrast-enhanced magnetic resonance imaging studies of the breast are frequently degraded by patient motion. In order to correct for this, any registration algorithm must overcome two major challenges: the highly deformable nature of the breast itself and the need to remove changes in signal intensity due to patient motion whilst leaving potentially significant changes in signal intensity due to changes in contrast agent concentration unchanged. In this paper, we evaluate the use of a non-rigid registration method that uses optical flow equations to drive the displacement of a grid of control points. With conventional optical flow techniques it is assumed that changes in image intensity are solely due to motion, making it unsuitable for use with contrast-enhanced studies. The registration algorithm evaluated in this paper overcomes this problem by including an additional term to account for changes in image intensity. Studies simulating physiologically plausible deformations of the breast together with realistic changes in contrast-enhancement derived from patient studies demonstrate that the algorithm is capable of registering images to sub-voxel accuracy within minutes. This technique has now been successfully incorporated into a breast cancer screening protocol allowing registered images to be provided routinely to the radiologist immediately after the scanning session.

Contribution of diffusion tensor MR imaging in detecting cerebral microstructural changes in adults with neurofibromatosis type 1.

After an early progression of signal intensity changes in T2-weighted MR images, also known as "neurofibromatosis bright objects," in patients with neurofibromatosis type 1 (NF-1), there is a tendency toward regression or even disappearance in early adulthood. The purpose of this study was to investigate whether adult patients with NF-1 exhibit generalized microstructural alterations even in normal-appearing brain regions. Conventional and diffusion tensor MR imaging of the brain was obtained in 10 adult patients with NF-1 and 10 age-matched healthy volunteers. Apparent diffusion coefficient (ADC) and fractional anisotropy (FA) were measured in brain stem, basal ganglia, thalamus, corpus callosum, and frontal and parietooccipital white matter regions. Significantly increased ADC and decreased FA values were found in all regions of interest and in all patients with NF-1, irrespective of their scholastic achievement and subsequent professional performance, compared with control subjects (P < .001). There were no significant correlations with the age (P > .1) or with the lateralization between brain hemispheres (P > .05). Diffusion tensor imaging reveals globally elevated FA and decreased ADC values in the mature brains of patients with NF-1, which is most likely a consequence of diffuse and basic alterations in cerebral microstructure that result from the underlying gene mutation.

Vision and Rain

The visual effects of rain are complex. Rain produces sharp intensity changes in images and videos that can severely impair the performance of outdoor vision systems. In this paper, we provide a comprehensive analysis of the visual effects of rain and the various factors that affect it. Based on this analysis, we develop efficient algorithms for handling rain in computer vision as well as for photorealistic rendering of rain in computer graphics. We first develop a photometric model that describes the intensities produced by individual rain streaks and a dynamic model that captures the spatio-temporal properties of rain. Together, these models describe the complete visual appearance of rain. Using these models, we develop a simple and effective post-processing algorithm for detection and removal of rain from videos. We show that our algorithm can distinguish rain from complex motion of scene objects and other time-varying textures. We then extend our analysis by studying how various factors such as camera parameters, rain properties and scene brightness affect the appearance of rain. We show that the unique physical properties of rain--its small size, high velocity and spatial distribution--makes its visibility depend strongly on camera parameters. This dependence is used to reduce the visibility of rain during image acquisition by judiciously selecting camera parameters. Conversely, camera parameters can also be chosen to enhance the visibility of rain. This ability can be used to develop an inexpensive and portable camera-based rain gauge that provides instantaneous rain-rate measurements. Finally, we develop a rain streak appearance model that accounts for the rapid shape distortions (i.e. oscillations) that a raindrop undergoes as it falls. We show that modeling these distortions allows us to faithfully render the complex intensity patterns that are visible in the case of raindrops that are close to the camera.

Cervical spondylotic myelopathy due to chronic compression: the role of signal intensity changes in magnetic resonance images

Although there is agreement that low-intensity signal changes on T1-weighted magnetic resonance (MR) images are a prognostic factor for poor outcome after surgical treatment of cervical myelopathy due to chronic cord compression, the role of high-intensity signal changes on T2-weighted images is still controversial. The aim of the present study was to determine whether T2-weighted MR imaging can help assess the prognosis of the disease. A prospective case series study was conducted. The population comprised 67 patients who underwent surgery between 1994 and 2004 to treat myelopathy caused by chronic cervical cord compression. The mean follow-up period was 39 months. Preoperative and postoperative functional status was evaluated using a modified Japanese Orthopaedic Association scale, and the recovery rate was calculated using the Hirabayashi method. Magnetic resonance images were acquired 3 months or less before surgery. High-intensity signal changes were evaluated according to the extent of these changes on T2-weighted sequences; low-intensity T1-weighted signal changes were also evaluated. In patients with low-intensity changes on T1-weighted images and in those with high-intensity changes spanning multiple levels on T2-weighted images, the authors documented a poor functional recovery. Multisegmental high-intensity change on T2-weighted MR imaging is a more sensitive indicator of outcomes than T1-weighted signal changes because of its higher frequency in patients with advanced myelopathy.

Early lung cancer detection based on registered perfusion MRI

Lung cancer remains the most common fatal malignancy in both men and women in the United States and elsewhere around the world among people who have been exposed passively or actively to tobacco smoke. Technological advances have produced imaging modalities that are proving to be useful for the early detection of lung cancer. In the usual modes, computed tomography (CT) and magnetic resonance imaging (MRI) can identify suspicious lesions, but further work is needed to detect cancer in its early stage. Tumor angiogenesis assessed by perfusion-sensitive MRI is a promising method for early and accurate identification of lung cancer that avoids patient stress and the potential progression to a less treatable stage inherent in serial imaging. However, compensating for the respiratory and anatomical structure motion is a challenge. In order to use perfusion MRI in a signal imaging session to define metabolic and vascular characteristics of tumors, we present a novel affine registration method for perfusion MRI that can register points of interest by tracking image intensity changes around the target point. The registration results are used to generate accurate time intensity curves (TIC) of different regions of interest (ROI). The patterns of different TICs are mapped on the cancer and other structures. The method is computationally efficient and performs well in our perfusion MRI sequence analysis.

Functional Magnetic Resonance Imaging in Conscious Animals: A New Tool in Behavioural Neuroscience Research

Functional magnetic resonance imaging (fMRI) is a unique window to the brain, enabling scientists to follow changes in brain activity in response to hormones, ageing, environment, drugs of abuse and other stimuli. There are two features that make fMRI unique when compared with other imaging modalities used in behavioural neuroscience. First, it can be entirely noninvasive: each animal can serve as its own control over the natural course of its life, vital for following neuroadaptation and other developmental processes critical to understanding behaviour. Second, fMRI has the spatial and temporal resolution to observe patterns of neuronal activity across the entire brain in less than a minute. Although fMRI does not have the cellular spatial resolution of immunostaining, nor the millisecond temporal resolution of electrophysiology, synchronised changes in neuronal activity across multiple brain areas seen with functional MRI can be viewed as functional neuroanatomical circuits coordinating the thoughts, memories and emotions for particular behaviours. Thus, fMRI affords a systems approach to the study of the brain, complementing and building from other neurobiological techniques to understand how behaviour is organised across multiple brain regions. In this review, we present a general background to fMRI and the different imaging modalities that can be used in fMRI studies. Included are examples of the application of fMRI in behavioural neuroscience research, along with discussion of the advantages and disadvantages of this technology.