Introduction of sensor spectral response into image fusion methods. Application to wavelet-based methods

Usual image fusion methods inject features from a high spatial resolution panchromatic sensor into every low spatial resolution multispectral band trying to preserve spectral signatures and improve spatial resolution to that of the panchromatic sensor. The objective is to obtain the image that would be observed by a sensor with the same spectral response (i.e., spectral sensitivity and quantum efficiency) as the multispectral sensors and the spatial resolution of the panchromatic sensor. But in these methods, features from electromagnetic spectrum regions not covered by multispectral sensors are injected into them, and physical spectral responses of the sensors are not considered during this process. This produces some undesirable effects, such as resolution overinjection images and slightly modified spectral signatures in some features. The authors present a technique which takes into account the physical electromagnetic spectrum responses of sensors during the fusion process, which produces images closer to the image obtained by the ideal sensor than those obtained by usual wavelet-based image fusion methods. This technique is used to define a new wavelet-based image fusion method.

Transfer insensitive labeling technique (TILT): application to multislice functional perfusion imaging.

Cerebral blood flow can be studied in a multislice mode with a recently proposed perfusion sequence using inversion of water spins as an endogenous tracer without magnetization transfer artifacts. The magnetization transfer insensitive labeling technique (TILT) has been used for mapping blood flow changes at a microvascular level under motor activation in a multislice mode. In TILT, perfusion mapping is achieved by subtraction of a perfusion-sensitized image from a control image. Perfusion weighting is accomplished by proximal blood labeling using two 90 degrees radiofrequency excitation pulses. For control preparation the labeling pulses are modified such that they have no net effect on blood water magnetization. The percentage of blood flow change, as well as its spatial extent, has been studied in single and multislice modes with varying delays between labeling and imaging. The average perfusion signal change due to activation was 36.9 +/- 9.1% in the single-slice experiments and 38.1 +/- 7.9% in the multislice experiments. The volume of activated brain areas amounted to 1.51 +/- 0.95 cm3 in the contralateral primary motor (M1) area, 0.90 +/- 0.72 cc in the ipsilateral M1 area, 1.27 +/- 0.39 cm3 in the contralateral and 1.42 +/- 0.75 cm3 in the ipsilateral premotor areas, and 0.71 +/- 0.19 cm3 in the supplementary motor area.

Using numerical classification of profiles based on Vis-NIR spectra to distinguish soils from the Piracicaba Region, Brazil

Considering that information from soil reflectance spectra is underutilized in soil classification, this paper aimed to evaluate the relationship of soil physical, chemical properties and their spectra, to identify spectral patterns for soil classes, evaluate the use of numerical classification of profiles combined with spectral data for soil classification. We studied 20 soil profiles from the municipality of Piracicaba, State of São Paulo, Brazil, which were morphologically described and classified up to the 3rd category level of the Brazilian Soil Classification System (SiBCS). Subsequently, soil samples were collected from pedogenetic horizons and subjected to soil particle size and chemical analyses. Their Vis-NIR spectra were measured, followed by principal component analysis. Pearson's linear correlation coefficients were determined among the four principal components and the following soil properties: pH, organic matter, P, K, Ca, Mg, Al, CEC, base saturation, and Al saturation. We also carried out interpretation of the first three principal components and their relationships with soil classes defined by SiBCS. In addition, numerical classification of the profiles based on the OSACA algorithm was performed using spectral data as a basis. We determined the Normalized Mutual Information (NMI) and Uncertainty Coefficient (U). These coefficients represent the similarity between the numerical classification and the soil classes from SiBCS. Pearson's correlation coefficients were significant for the principal components when compared to sand, clay, Al content and soil color. Visual analysis of the principal component scores showed differences in the spectral behavior of the soil classes, mainly among Argissolos and the others soils. The NMI and U similarity coefficients showed values of 0.74 and 0.64, respectively, suggesting good similarity between the numerical and SiBCS classes. For example, numerical classification correctly distinguished Argissolos from Latossolos and Nitossolos. However, this mathematical technique was not able to distinguish Latossolos from Nitossolos Vermelho férricos, but the Cambissolos were well differentiated from other soil classes. The numerical technique proved to be effective and applicable to the soil classification process.

Identification of different heart tissues from MRI C-SENC images using an unsupervised multi-stage fuzzy clustering technique.

PURPOSE: To objectively characterize different heart tissues from functional and viability images provided by composite-strain-encoding (C-SENC) MRI. MATERIALS AND METHODS: C-SENC is a new MRI technique for simultaneously acquiring cardiac functional and viability images. In this work, an unsupervised multi-stage fuzzy clustering method is proposed to identify different heart tissues in the C-SENC images. The method is based on sequential application of the fuzzy c-means (FCM) and iterative self-organizing data (ISODATA) clustering algorithms. The proposed method is tested on simulated heart images and on images from nine patients with and without myocardial infarction (MI). The resulting clustered images are compared with MRI delayed-enhancement (DE) viability images for determining MI. Also, Bland-Altman analysis is conducted between the two methods. RESULTS: Normal myocardium, infarcted myocardium, and blood are correctly identified using the proposed method. The clustered images correctly identified 90 +/- 4% of the pixels defined as infarct in the DE images. In addition, 89 +/- 5% of the pixels defined as infarct in the clustered images were also defined as infarct in DE images. The Bland-Altman results show no bias between the two methods in identifying MI. CONCLUSION: The proposed technique allows for objectively identifying divergent heart tissues, which would be potentially important for clinical decision-making in patients with MI.

ZHARP: three-dimensional motion tracking from a single image plane.

Three-dimensional imaging and quantification of myocardial function are essential steps in the evaluation of cardiac disease. We propose a tagged magnetic resonance imaging methodology called zHARP that encodes and automatically tracks myocardial displacement in three dimensions. Unlike other motion encoding techniques, zHARP encodes both in-plane and through-plane motion in a single image plane without affecting the acquisition speed. Postprocessing unravels this encoding in order to directly track the 3-D displacement of every point within the image plane throughout an entire image sequence. Experimental results include a phantom validation experiment, which compares zHARP to phase contrast imaging, and an in vivo study of a normal human volunteer. Results demonstrate that the simultaneous extraction of in-plane and through-plane displacements from tagged images is feasible.

Digital holographic microscopy: a noninvasive contrast imaging technique allowing quantitative visualization of living cells with subwavelength axial accuracy.

We have developed a digital holographic microscope (DHM), in a transmission mode, especially dedicated to the quantitative visualization of phase objects such as living cells. The method is based on an original numerical algorithm presented in detail elsewhere [Cuche et al., Appl. Opt. 38, 6994 (1999)]. DHM images of living cells in culture are shown for what is to our knowledge the first time. They represent the distribution of the optical path length over the cell, which has been measured with subwavelength accuracy. These DHM images are compared with those obtained by use of the widely used phase contrast and Nomarski differential interference contrast techniques.

MDCT arthrography of the hip: value of the adaptive statistical iterative reconstruction technique and potential for radiation dose reduction.

OBJECTIVE: The purpose of this article is to assess the effect of the adaptive statistical iterative reconstruction (ASIR) technique on image quality in hip MDCT arthrography and to evaluate its potential for reducing radiation dose. SUBJECTS AND METHODS: Thirty-seven patients examined with hip MDCT arthrography were prospectively randomized into three different protocols: one with a regular dose (volume CT dose index [CTDIvol], 38.4 mGy) and two with a reduced dose (CTDIvol, 24.6 or 15.4 mGy). Images were reconstructed using filtered back projection (FBP) and four increasing percentages of ASIR (30%, 50%, 70%, and 90%). Image noise and contrast-to-noise ratio (CNR) were measured. Two musculoskeletal radiologists independently evaluated several anatomic structures and image quality parameters using a 4-point scale. They also jointly assessed acetabular labrum tears and articular cartilage lesions. RESULTS: With decreasing radiation dose level, image noise statistically significantly increased (p=0.0009) and CNR statistically significantly decreased (p=0.001). We also found a statistically significant reduction in noise (p=0.0001) and increase in CNR (p≤0.003) with increasing percentage of ASIR; in addition, we noted statistically significant increases in image quality scores for the labrum and cartilage, subchondral bone, overall diagnostic quality (up to 50% ASIR), and subjective noise (p≤0.04), and statistically significant reductions for the trabecular bone and muscles (p≤0.03). Regardless of the radiation dose level, there were no statistically significant differences in the detection and characterization of labral tears (n=24; p=1) and cartilage lesions (n=40; p≥0.89) depending on the ASIR percentage. CONCLUSION: The use of up to 50% ASIR in hip MDCT arthrography helps to reduce radiation dose by approximately 35-60%, while maintaining diagnostic image quality comparable to that of a regular-dose protocol using FBP.

Monitoring network optimisation for spatial data classification using support vector machines

The paper presents a novel method for monitoring network optimisation, based on a recent machine learning technique known as support vector machine. It is problem-oriented in the sense that it directly answers the question of whether the advised spatial location is important for the classification model. The method can be used to increase the accuracy of classification models by taking a small number of additional measurements. Traditionally, network optimisation is performed by means of the analysis of the kriging variances. The comparison of the method with the traditional approach is presented on a real case study with climate data.

Free-breathing 3D coronary MRA: the impact of "isotropic" image resolution.

During conventional x-ray coronary angiography, multiple projections of the coronary arteries are acquired to define coronary anatomy precisely. Due to time constraints, coronary magnetic resonance angiography (MRA) usually provides only one or two views of the major coronary vessels. A coronary MRA approach that allowed for reconstruction of arbitrary isotropic orientations might therefore be desirable. The purpose of the study was to develop a three-dimensional (3D) coronary MRA technique with isotropic image resolution in a relatively short scanning time that allows for reconstruction of arbitrary views of the coronary arteries without constraints given by anisotropic voxel size. Eight healthy adult subjects were examined using a real-time navigator-gated and corrected free-breathing interleaved echoplanar (TFE-EPI) 3D-MRA sequence. Two 3D datasets were acquired for the left and right coronary systems in each subject, one with anisotropic (1.0 x 1.5 x 3.0 mm, 10 slices) and one with "near" isotropic (1.0 x 1.5 x 1.0 mm, 30 slices) image resolution. All other imaging parameters were maintained. In all cases, the entire left main (LM) and extensive portions of the left anterior descending (LAD) and the right coronary artery (RCA) were visualized. Objective assessment of coronary vessel sharpness was similar (41% +/- 5% vs. 42% +/- 5%; P = NS) between in-plane and through-plane views with "isotropic" voxel size but differed (32% +/- 7% vs. 23% +/- 4%; P < 0.001) with nonisotropic voxel size. In reconstructed views oriented in the through-plane direction, the vessel border was 86% more defined (P < 0.01) for isotropic compared with anisotropic images. A smaller (30%; P < 0.001) improvement was seen for in-plane reconstructions. Vessel diameter measurements were view independent (2.81 +/- 0.45 mm vs. 2.66 +/- 0.52 mm; P = NS) for isotropic, but differed (2.71 +/- 0.51 mm vs. 3.30 +/- 0.38 mm; P < 0.001) between anisotropic views. Average scanning time was 2:31 +/- 0:57 minutes for anisotropic and 7:11 +/- 3:02 minutes for isotropic image resolution (P < 0.001). We present a new approach for "near" isotropic 3D coronary artery imaging, which allows for reconstruction of arbitrary views of the coronary arteries. The good delineation of the coronary arteries in all views suggests that isotropic 3D coronary MRA might be a preferred technique for the assessment of coronary disease, although at the expense of prolonged scan times. Comparative studies with conventional x-ray angiography are needed to investigate the clinical utility of the isotropic strategy.

Statistical assessment of dataset shift and model portability in multi-angle in-track image acquisitions

In this study we propose an evaluation of the angular effects altering the spectral response of the land-cover over multi-angle remote sensing image acquisitions. The shift in the statistical distribution of the pixels observed in an in-track sequence of WorldView-2 images is analyzed by means of a kernel-based measure of distance between probability distributions. Afterwards, the portability of supervised classifiers across the sequence is investigated by looking at the evolution of the classification accuracy with respect to the changing observation angle. In this context, the efficiency of various physically and statistically based preprocessing methods in obtaining angle-invariant data spaces is compared and possible synergies are discussed.

Inexperienced sonographers can successfully visualize and assess a three-dimensional image of the fetal face using a standardized ultrasound protocol.

Introduction: A standardized three-dimensional ultrasonographic (3DUS) protocol is described that allows fetal face reconstruction. Ability to identify cleft lip with 3DUS using this protocol was assessed by operators with minimal 3DUS experience. Material and Methods: 260 stored volumes of fetal face were analyzed using a standardized protocol by operators with different levels of competence in 3DUS. The outcomes studied were: (1) the performance of post-processing 3D face volumes for the detection of facial clefts; (2) the ability of a resident with minimal 3DUS experience to reconstruct the acquired facial volumes, and (3) the time needed to reconstruct each plane to allow proper diagnosis of a cleft. Results: The three orthogonal planes of the fetal face (axial, sagittal and coronal) were adequately reconstructed with similar performance when acquired by a maternal-fetal medicine specialist or by residents with minimal experience (72 vs. 76%, p = 0.629). The learning curve for manipulation of 3DUS volumes of the fetal face corresponds to 30 cases and is independent of the operator's level of experience. Discussion: The learning curve for the standardized protocol we describe is short, even for inexperienced sonographers. This technique might decrease the length of anatomy ultrasounds and improve the ability to visualize fetal face anomalies.

Improved multiple-locus variable-number tandem-repeat assay for Staphylococcus aureus genotyping, providing a highly informative technique together with strong phylogenetic value.

We describe an improved multiple-locus variable-number tandem-repeat (VNTR) analysis (MLVA) scheme for genotyping Staphylococcus aureus. We compare its performance to those of multilocus sequence typing (MLST) and spa typing in a survey of 309 strains. This collection includes 87 epidemic methicillin-resistant S. aureus (MRSA) strains of the Harmony collection, 75 clinical strains representing the major MLST clonal complexes (CCs) (50 methicillin-sensitive S. aureus [MSSA] and 25 MRSA), 135 nasal carriage strains (133 MSSA and 2 MRSA), and 13 published S. aureus genome sequences. The results show excellent concordance between the techniques' results and demonstrate that the discriminatory power of MLVA is higher than those of both MLST and spa typing. Two hundred forty-two genotypes are discriminated with 14 VNTR loci (diversity index, 0.9965; 95% confidence interval, 0.9947 to 0.9984). Using a cutoff value of 45%, 21 clusters are observed, corresponding to the CCs previously defined by MLST. The variability of the different tandem repeats allows epidemiological studies, as well as follow-up of the evolution of CCs and the identification of potential ancestors. The 14 loci can conveniently be analyzed in two steps, based upon a first-line simplified assay comprising a subset of 10 loci (panel 1) and a second subset of 4 loci (panel 2) that provides higher resolution when needed. In conclusion, the MLVA scheme proposed here, in combination with available on-line genotyping databases (including http://mlva.u-psud.fr/), multiplexing, and automatic sizing, can provide a basis for almost-real-time large-scale population monitoring of S. aureus.

Image Analysis for Evaluating Air Void Parameters of Concrete, HR-396, 1998

This research project investigated the use of image analysis to measure the air void parameters of concrete specimens produced under standard laboratory conditions. The results obtained from the image analysis technique were compared to results obtained from plastic air content tests, Danish air meter tests (also referred to as Air Void Analyzer tests), high-pressure air content tests on hardened concrete, and linear traverse tests (as per ASTM C-457). Hardened concrete specimens were sent to three different laboratories for the linear traverse tests. The samples that were circulated to the three labs consisted of specimens that needed different levels of surface preparation. The first set consisted of approximately 18 specimens that had been sectioned from a 4 in. by 4 in. by 18 in. (10 cm by 10 cm by 46 cm) beam using a saw equipped with a diamond blade. These specimens were subjected to the normal sample preparation techniques that were commonly employed by the three different labs (each lab practiced slightly different specimen preparation techniques). The second set of samples consisted of eight specimens that had been ground and polished at a single laboratory. The companion labs were only supposed to retouch the sample surfaces if they exhibited major flaws. In general, the study indicated that the image analysis test results for entrained air content exhibited good to strong correlation to the average values determined via the linear traverse technique. Specimens ground and polished in a single laboratory and then circulated to the other participating laboratories for the air content determinations exhibited the strongest correlation between the image analysis and linear traverse techniques (coefficient of determination, r-squared = 0.96, for n=8). Specimens ground and polished at each of the individual laboratories exhibited considerably more scatter (coefficient of determination, r-squared = 0.78, for n=16). The image analysis technique tended to produce low estimates of the specific surface of the voids when compared to the results from the linear traverse method. This caused the image analysis spacing factor calculations to produce larger values than those obtained from the linear traverse tests. The image analysis spacing factors were still successful at distinguishing between the frost-prone test specimens and the other (more durable) test specimens that were studied in this research project.

Transmission electron microscopy in cell biology: sample preparation techniques and image information

Transmission electron microscopy is a proven technique in the field of cell biology and a very useful tool in biomedical research. Innovation and improvements in equipment together with the introduction of new technology have allowed us to improve our knowledge of biological tissues, to visualizestructures better and both to identify and to locate molecules. Of all the types ofmicroscopy exploited to date, electron microscopy is the one with the mostadvantageous resolution limit and therefore it is a very efficient technique fordeciphering the cell architecture and relating it to function. This chapter aims toprovide an overview of the most important techniques that we can apply to abiological sample, tissue or cells, to observe it with an electron microscope, fromthe most conventional to the latest generation. Processes and concepts aredefined, and the advantages and disadvantages of each technique are assessedalong with the image and information that we can obtain by using each one ofthem.

Recent advances in remote sensing image processing

Remote sensing image processing is nowadays a mature research area. The techniques developed in the field allow many real-life applications with great societal value. For instance, urban monitoring, fire detection or flood prediction can have a great impact on economical and environmental issues. To attain such objectives, the remote sensing community has turned into a multidisciplinary field of science that embraces physics, signal theory, computer science, electronics, and communications. From a machine learning and signal/image processing point of view, all the applications are tackled under specific formalisms, such as classification and clustering, regression and function approximation, image coding, restoration and enhancement, source unmixing, data fusion or feature selection and extraction. This paper serves as a survey of methods and applications, and reviews the last methodological advances in remote sensing image processing.