How to set up and apply reference levels in fluoroscopy at a national level.

A nationwide survey was launched to investigate the use of fluoroscopy and establish national reference levels (RL) for dose-intensive procedures. The 2-year investigation covered five radiology and nine cardiology departments in public hospitals and private clinics, and focused on 12 examination types: 6 diagnostic and 6 interventional. A total of 1,000 examinations was registered. Information including the fluoroscopy time (T), the number of frames (N) and the dose-area product (DAP) was provided. The data set was used to establish the distributions of T, N and the DAP and the associated RL values. The examinations were pooled to improve the statistics. A wide variation in dose and image quality in fixed geometry was observed. As an example, the skin dose rate for abdominal examinations varied in the range of 10 to 45 mGy/min for comparable image quality. A wide variability was found for several types of examinations, mainly complex ones. DAP RLs of 210, 125, 80, 240, 440 and 110 Gy cm2 were established for lower limb and iliac angiography, cerebral angiography, coronary angiography, biliary drainage and stenting, cerebral embolization and PTCA, respectively. The RL values established are compared to the data published in the literature.

Generating controlled image sets in cognitive neuroscience research.

The investigation of perceptual and cognitive functions with non-invasive brain imaging methods critically depends on the careful selection of stimuli for use in experiments. For example, it must be verified that any observed effects follow from the parameter of interest (e.g. semantic category) rather than other low-level physical features (e.g. luminance, or spectral properties). Otherwise, interpretation of results is confounded. Often, researchers circumvent this issue by including additional control conditions or tasks, both of which are flawed and also prolong experiments. Here, we present some new approaches for controlling classes of stimuli intended for use in cognitive neuroscience, however these methods can be readily extrapolated to other applications and stimulus modalities. Our approach is comprised of two levels. The first level aims at equalizing individual stimuli in terms of their mean luminance. Each data point in the stimulus is adjusted to a standardized value based on a standard value across the stimulus battery. The second level analyzes two populations of stimuli along their spectral properties (i.e. spatial frequency) using a dissimilarity metric that equals the root mean square of the distance between two populations of objects as a function of spatial frequency along x- and y-dimensions of the image. Randomized permutations are used to obtain a minimal value between the populations to minimize, in a completely data-driven manner, the spectral differences between image sets. While another paper in this issue applies these methods in the case of acoustic stimuli (Aeschlimann et al., Brain Topogr 2008), we illustrate this approach here in detail for complex visual stimuli.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

MSight: an image analysis software for liquid chromatography-mass spectrometry.

Images obtained from high-throughput mass spectrometry (MS) contain information that remains hidden when looking at a single spectrum at a time. Image processing of liquid chromatography-MS datasets can be extremely useful for quality control, experimental monitoring and knowledge extraction. The importance of imaging in differential analysis of proteomic experiments has already been established through two-dimensional gels and can now be foreseen with MS images. We present MSight, a new software designed to construct and manipulate MS images, as well as to facilitate their analysis and comparison.

Structured output SVM for remote sensing image classification

In the recent years, kernel methods have revealed very powerful tools in many application domains in general and in remote sensing image classification in particular. The special characteristics of remote sensing images (high dimension, few labeled samples and different noise sources) are efficiently dealt with kernel machines. In this paper, we propose the use of structured output learning to improve remote sensing image classification based on kernels. Structured output learning is concerned with the design of machine learning algorithms that not only implement input-output mapping, but also take into account the relations between output labels, thus generalizing unstructured kernel methods. We analyze the framework and introduce it to the remote sensing community. Output similarity is here encoded into SVM classifiers by modifying the model loss function and the kernel function either independently or jointly. Experiments on a very high resolution (VHR) image classification problem shows promising results and opens a wide field of research with structured output kernel methods.

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.

Copper filtration in pediatric digital X-ray imaging: its impact on image quality and dose.

The effect of copper (Cu) filtration on image quality and dose in different digital X-ray systems was investigated. Two computed radiography systems and one digital radiography detector were used. Three different polymethylmethacrylate blocks simulated the pediatric body. The effect of Cu filters of 0.1, 0.2, and 0.3 mm thickness on the entrance surface dose (ESD) and the corresponding effective doses (EDs) were measured at tube voltages of 60, 66, and 73 kV. Image quality was evaluated in a contrast-detail phantom with an automated analyzer software. Cu filters of 0.1, 0.2, and 0.3 mm thickness decreased the ESD by 25-32%, 32-39%, and 40-44%, respectively, the ranges depending on the respective tube voltages. There was no consistent decline in image quality due to increasing Cu filtration. The estimated ED of anterior-posterior (AP) chest projections was reduced by up to 23%. No relevant reduction in the ED was noted in AP radiographs of the abdomen and pelvis or in posterior-anterior radiographs of the chest. Cu filtration reduces the ESD, but generally does not reduce the effective dose. Cu filters can help protect radiosensitive superficial organs, such as the mammary glands in AP chest projections.

How Low Can We Go in Contrast-Enhanced CT Imaging of the Chest?: A Dose-Finding Cadaver Study Using the Model-based Iterative Image Reconstruction Approach.

RATIONALE AND OBJECTIVES: Dose reduction may compromise patients because of a decrease of image quality. Therefore, the amount of dose savings in new dose-reduction techniques needs to be thoroughly assessed. To avoid repeated studies in one patient, chest computed tomography (CT) scans with different dose levels were performed in corpses comparing model-based iterative reconstruction (MBIR) as a tool to enhance image quality with current standard full-dose imaging. MATERIALS AND METHODS: Twenty-five human cadavers were scanned (CT HD750) after contrast medium injection at different, decreasing dose levels D0-D5 and respectively reconstructed with MBIR. The data at full-dose level, D0, have been additionally reconstructed with standard adaptive statistical iterative reconstruction (ASIR), which represented the full-dose baseline reference (FDBR). Two radiologists independently compared image quality (IQ) in 3-mm multiplanar reformations for soft-tissue evaluation of D0-D5 to FDBR (-2, diagnostically inferior; -1, inferior; 0, equal; +1, superior; and +2, diagnostically superior). For statistical analysis, the intraclass correlation coefficient (ICC) and the Wilcoxon test were used. RESULTS: Mean CT dose index values (mGy) were as follows: D0/FDBR = 10.1 ± 1.7, D1 = 6.2 ± 2.8, D2 = 5.7 ± 2.7, D3 = 3.5 ± 1.9, D4 = 1.8 ± 1.0, and D5 = 0.9 ± 0.5. Mean IQ ratings were as follows: D0 = +1.8 ± 0.2, D1 = +1.5 ± 0.3, D2 = +1.1 ± 0.3, D3 = +0.7 ± 0.5, D4 = +0.1 ± 0.5, and D5 = -1.2 ± 0.5. All values demonstrated a significant difference to baseline (P < .05), except mean IQ for D4 (P = .61). ICC was 0.91. CONCLUSIONS: Compared to ASIR, MBIR allowed for a significant dose reduction of 82% without impairment of IQ. This resulted in a calculated mean effective dose below 1 mSv.

A study of the cambial zone and conductive phloem of common beech (Fagus sylvatica L.) using an image analysis method. I. Influence of tree age on the structure

Quantification is a major problem when using histology to study the influence of ecological factors on tree structure. This paper presents a method to prepare and to analyse transverse sections of cambial zone and of conductive phloem in bark samples. The following paper (II) presents the automated measurement procedure. Part I here describes and discusses the preparation method, and the influence of tree age on the observed structure. Highly contrasted images of samples extracted at breast height during dormancy were analysed with an automatic image analyser. Between three young (38 years) and three old (147 years) trees, age-related differences were identified by size and shape parameters, at both cell and tissue levels. In the cambial zone, older trees had larger and more rectangular fusiform initials. In the phloem, sieve tubes were also larger, but their shape did not change and the area for sap conduction was similar in both categories. Nevertheless, alterations were limited, and demanded statistical analysis to be identified and ascertained. The physiological implications of the structural changes are discussed.

Trabecular Bone Score: A Noninvasive Analytical Method Based Upon the DXA Image.

The trabecular bone score (TBS) is a gray-level textural metric that can be extracted from the two-dimensional lumbar spine dual-energy X-ray absorptiometry (DXA) image. TBS is related to bone microarchitecture and provides skeletal information that is not captured from the standard bone mineral density (BMD) measurement. Based on experimental variograms of the projected DXA image, TBS has the potential to discern differences between DXA scans that show similar BMD measurements. An elevated TBS value correlates with better skeletal microstructure; a low TBS value correlates with weaker skeletal microstructure. Lumbar spine TBS has been evaluated in cross-sectional and longitudinal studies. The following conclusions are based upon publications reviewed in this article: 1) TBS gives lower values in postmenopausal women and in men with previous fragility fractures than their nonfractured counterparts; 2) TBS is complementary to data available by lumbar spine DXA measurements; 3) TBS results are lower in women who have sustained a fragility fracture but in whom DXA does not indicate osteoporosis or even osteopenia; 4) TBS predicts fracture risk as well as lumbar spine BMD measurements in postmenopausal women; 5) efficacious therapies for osteoporosis differ in the extent to which they influence the TBS; 6) TBS is associated with fracture risk in individuals with conditions related to reduced bone mass or bone quality. Based on these data, lumbar spine TBS holds promise as an emerging technology that could well become a valuable clinical tool in the diagnosis of osteoporosis and in fracture risk assessment. © 2014 American Society for Bone and Mineral Research.

Is accurate perception of body image associated with appropriate weight-control behavior among adolescents of the Seychelles

BACKGROUND: We examined body image perception and its association with reported weight-control behavior among adolescents in the Seychelles.METHODS: We conducted a school-based survey of 1432 students aging 11-17 years in the Seychelles. Perception of body image was assessed using both a closed-ended question (CEQ) and Stunkard's pictorial silhouettes (SPS). Voluntary attempts to change weight were also assessed.RESULTS: A substantial proportion of the overweight students did not consider themselves as overweight (SPS: 24%, CEQ: 34%), and a substantial proportion of the normal-weight students considered themselves as too thin (SPS: 29%, CEQ: 15%). Logistic regression analysis showed that students with an accurate weight perception were more likely to have appropriate weight-control behavior.CONCLUSIONS: We found that substantial proportions of students had an inaccurate perception of their weight and that weight perception was associated with weight-control behavior. These findings point to forces that can drive the upwards overweight trends.

Survey on image quality and dose levels used in Europe for mammography.

Quality assurance programmes are becoming a common practice in the field of mammography. At the present time several recommendations exist and different test objects are used to optimize this radiological procedure. The goal of this study was to check if geographically distant centres using different quality control procedures were comparable when using a common objective way of assessing image quality. The results show that consensus still needs to be found among radiologists to reach a satisfactory level of harmony between patient doses and image quality in Europe.

An image quality comparison of standard and dual-side read CR systems for pediatric radiology.

An objective analysis of image quality parameters was performed for a computed radiography (CR) system using both standard single-side and prototype dual-side read plates. The pre-sampled modulation transfer function (MTF), noise power spectrum (NPS), and detective quantum efficiency (DQE) for the systems were determined at three different beam qualities representative of pediatric chest radiography, at an entrance detector air kerma of 5 microGy. The NPS and DQE measurements were realized under clinically relevant x-ray spectra for pediatric radiology, including x-ray scatter radiations. Compared to the standard single-side read system, the MTF for the dual-side read system is reduced, but this is offset by a significant decrease in image noise, resulting in a marked increase in DQE (+40%) in the low spatial frequency range. Thus, for the same image quality, the new technology permits the CR system to be used at a reduced dose level.

Objective comparison of image quality and dose between conventional and synchrotron radiation mammography.

The shape of the energy spectrum produced by an x-ray tube has a great importance in mammography. Many anode-filtration combinations have been proposed to obtain the most effective spectrum shape for the image quality-dose relationship. On the other hand, third generation synchrotrons such as the European Synchrotron Radiation Facility in Grenoble are able to produce a high flux of monoenergetic radiation. It is thus a powerful tool to study the effect of beam energy on image quality and dose in mammography. An objective method was used to evaluate image quality and dose in mammography with synchrotron radiation and to compare them to standard conventional units. It was performed systematically in the energy range of interest for mammography through the evaluation of a global image quality index and through the measurement of the mean glandular dose. Compared to conventional mammography units, synchrotron radiation shows a great improvement of the image quality-dose relationship, which is due to the beam monochromaticity and to the high intrinsic collimation of the beam, which allows the use of a slit instead of an anti-scatter grid for scatter rejection.

Exploration of alpine orographic precipitation patterns with radar image processing and clustering techniques

A methodology of exploratory data analysis investigating the phenomenon of orographic precipitation enhancement is proposed. The precipitation observations obtained from three Swiss Doppler weather radars are analysed for the major precipitation event of August 2005 in the Alps. Image processing techniques are used to detect significant precipitation cells/pixels from radar images while filtering out spurious effects due to ground clutter. The contribution of topography to precipitation patterns is described by an extensive set of topographical descriptors computed from the digital elevation model at multiple spatial scales. Additionally, the motion vector field is derived from subsequent radar images and integrated into a set of topographic features to highlight the slopes exposed to main flows. Following the exploratory data analysis with a recent algorithm of spectral clustering, it is shown that orographic precipitation cells are generated under specific flow and topographic conditions. Repeatability of precipitation patterns in particular spatial locations is found to be linked to specific local terrain shapes, e.g. at the top of hills and on the upwind side of the mountains. This methodology and our empirical findings for the Alpine region provide a basis for building computational data-driven models of orographic enhancement and triggering of precipitation. Copyright (C) 2011 Royal Meteorological Society .