Detection of ingested cocaine-filled packets: comparison of filtered back projection CT with adaptive statistical iterative reconstructed images

Purpose: To evaluate the diagnostic value and image quality of CT with filtered back projection (FBP) compared with adaptive statistical iterative reconstructed images (ASIR) in body stuffers with ingested cocaine-filled packets.Methods and Materials: Twenty-nine body stuffers (mean age 31.9 years, 3 women) suspected for ingestion of cocaine-filled packets underwent routine-dose 64-row multidetector CT with FBP (120kV, pitch 1.375, 100-300 mA and automatic tube current modulation (auto mA), rotation time 0.7sec, collimation 2.5mm), secondarily reconstructed with 30 % and 60 % ASIR. In 13 (44.83%) out of the body stuffers cocaine-filled packets were detected, confirmed by exact analysis of the faecal content including verification of the number (range 1-25). Three radiologists independently and blindly evaluated anonymous CT examinations (29 FBP-CT and 68 ASIR-CT) for the presence and number of cocaine-filled packets indicating observers' confidence, and graded them for diagnostic quality, image noise, and sharpness. Sensitivity, specificity, area under the receiver operating curve (ROC) Az and interobserver agreement between the 3 radiologists for FBP-CT and ASIR-CT were calculated.Results: The increase of the percentage of ASIR significantly diminished the objective image noise (p<0.001). Overall sensitivity and specificity for the detection of the cocaine-filled packets were 87.72% and 76.15%, respectively. The difference of ROC area Az between the different reconstruction techniques was significant (p= 0.0101), that is 0.938 for FBP-CT, 0.916 for 30 % ASIR-CT, and 0.894 for 60 % ASIR-CT.Conclusion: Despite the evident image noise reduction obtained by ASIR, the diagnostic value for detecting cocaine-filled packets decreases, depending on the applied ASIR percentage.

Cluster kernels for semisupervised classification of VHR urban images

In this paper, we present and apply a semisupervised support vector machine based on cluster kernels for the problem of very high resolution image classification. In the proposed setting, a base kernel working with labeled samples only is deformed by a likelihood kernel encoding similarities between unlabeled examples. The resulting kernel is used to train a standard support vector machine (SVM) classifier. Experiments carried out on very high resolution (VHR) multispectral and hyperspectral images using very few labeled examples show the relevancy of the method in the context of urban image classification. Its simplicity and the small number of parameters involved make it versatile and workable by unexperimented users.

Estimation of the lateral correlation structure of subsurface water content from surface-based ground-penetrating radar reflection images

Over the past decade, significant interest has been expressed in relating the spatial statistics of surface-based reflection ground-penetrating radar (GPR) data to those of the imaged subsurface volume. A primary motivation for this work is that changes in the radar wave velocity, which largely control the character of the observed data, are expected to be related to corresponding changes in subsurface water content. Although previous work has indeed indicated that the spatial statistics of GPR images are linked to those of the water content distribution of the probed region, a viable method for quantitatively analyzing the GPR data and solving the corresponding inverse problem has not yet been presented. Here we address this issue by first deriving a relationship between the 2-D autocorrelation of a water content distribution and that of the corresponding GPR reflection image. We then show how a Bayesian inversion strategy based on Markov chain Monte Carlo sampling can be used to estimate the posterior distribution of subsurface correlation model parameters that are consistent with the GPR data. Our results indicate that if the underlying assumptions are valid and we possess adequate prior knowledge regarding the water content distribution, in particular its vertical variability, this methodology allows not only for the reliable recovery of lateral correlation model parameters but also for estimates of parameter uncertainties. In the case where prior knowledge regarding the vertical variability of water content is not available, the results show that the methodology still reliably recovers the aspect ratio of the heterogeneity.

Contrast ultrasound: a simple-to-use phase-shifting medium offers saline infusion sonography-like images.

OBJECTIVE: To test the ability of a novel phase-shifting medium (PSM) to provide sustained distension of the uterine cavity and produce saline infusion sonography (SIS)-like images in a simplified contrast ultrasound procedure. DESIGN: Prospective pilot feasibility trial of a new diagnostic procedure, contrast ultrasound. SETTING: Clinical reproductive endocrine and infertility unit of regional teaching hospital. PATIENT(S): Twenty-six asymptomatic infertile women (group I) and 27 women presenting with dysfunctional uterine bleeding (DUB) who were scheduled for exploratory surgery (group II). INTERVENTION(S): All women who were temporarily on oral contraceptive first had a regular pelvic ultrasound followed by the intrauterine instillation of up to 3 mL PSM, using a regular insemination catheter, after which all instruments were removed and a regular ultrasound was performed again. RESULT(S): In all 53 women, intrauterine instillation of 1-3 mL PSM resulted in a 3-7 mm uterine distension, sufficient to produce SIS-like images of the uterine cavity that lasted 7-10 min. Contrast ultrasound revealed an endometrial polyp in 3 asymptomatic women of group I. In group II. 12 of 14 women (86%) whose vaginal ultrasound were positive or dubious had positive findings with contrast ultrasound; 9 of 12 patients whose vaginal ultrasounds were negative also had positive contrast ultrasound findings. All the positive and negative findings of contrast ultrasound made in group II were confirmed anatomically (sensitivity and specificity of 100%), whereas the correlation for standard vaginal ultrasound was markedly lower at 57.1% and 85.7%, respectively. Most patients (46 of 53) reported no discomfort during or after the procedure, and 7 women described the procedure as mildly uncomfortable. CONCLUSION(S): Contrast ultrasound, a novel simple diagnostic procedure conducted after intrauterine instillation of 1-3 mL PSM using a simple plastic catheter, delivered SIS-quality images in asymptomatic (group I) and symptomatic (group II) patients while retaining the simplicity of standard ultrasound. We therefore foresee broad application of contrast ultrasound for sensitive and specific assessment for uterine pathologies in the physician's office.

Brain tissue segmentation of fetal MR images

We present a segmentation method for fetal brain tissuesof T2w MR images, based on the well known ExpectationMaximization Markov Random Field (EM- MRF) scheme. Ourmain contribution is an intensity model composed of 7Gaussian distribution designed to deal with the largeintensity variability of fetal brain tissues. The secondmain contribution is a 3-steps MRF model that introducesboth local spatial and anatomical priors given by acortical distance map. Preliminary results on 4 subjectsare presented and evaluated in comparison to manualsegmentations showing that our methodology cansuccessfully be applied to such data, dealing with largeintensity variability within brain tissues and partialvolume (PV).

Kernel-based methods for change detection in remote sensing images

Nowadays, the joint exploitation of images acquired daily by remote sensing instruments and of images available from archives allows a detailed monitoring of the transitions occurring at the surface of the Earth. These modifications of the land cover generate spectral discrepancies that can be detected via the analysis of remote sensing images. Independently from the origin of the images and of type of surface change, a correct processing of such data implies the adoption of flexible, robust and possibly nonlinear method, to correctly account for the complex statistical relationships characterizing the pixels of the images. This Thesis deals with the development and the application of advanced statistical methods for multi-temporal optical remote sensing image processing tasks. Three different families of machine learning models have been explored and fundamental solutions for change detection problems are provided. In the first part, change detection with user supervision has been considered. In a first application, a nonlinear classifier has been applied with the intent of precisely delineating flooded regions from a pair of images. In a second case study, the spatial context of each pixel has been injected into another nonlinear classifier to obtain a precise mapping of new urban structures. In both cases, the user provides the classifier with examples of what he believes has changed or not. In the second part, a completely automatic and unsupervised method for precise binary detection of changes has been proposed. The technique allows a very accurate mapping without any user intervention, resulting particularly useful when readiness and reaction times of the system are a crucial constraint. In the third, the problem of statistical distributions shifting between acquisitions is studied. Two approaches to transform the couple of bi-temporal images and reduce their differences unrelated to changes in land cover are studied. The methods align the distributions of the images, so that the pixel-wise comparison could be carried out with higher accuracy. Furthermore, the second method can deal with images from different sensors, no matter the dimensionality of the data nor the spectral information content. This opens the doors to possible solutions for a crucial problem in the field: detecting changes when the images have been acquired by two different sensors.

Atlas-based segmentation of pathological brain MR images

We propose a method for brain atlas deformation inpresence of large space-occupying tumors, based on an apriori model of lesion growth that assumes radialexpansion of the lesion from its starting point. First,an affine registration brings the atlas and the patientinto global correspondence. Then, the seeding of asynthetic tumor into the brain atlas provides a templatefor the lesion. Finally, the seeded atlas is deformed,combining a method derived from optical flow principlesand a model of lesion growth (MLG). Results show that themethod can be applied to the automatic segmentation ofstructures and substructures in brains with grossdeformation, with important medical applications inneurosurgery, radiosurgery and radiotherapy.

Quality Assessment of Cardiac Magnetic Resonance Images at 1.5/3.0 T: Description and Validation of Standardized Criteria

PURPOSE: Cardiovascular magnetic resonance (CMR) has become a robust and important diagnostic imaging modality in cardiovascular medicine. However,insufficient image quality may compromise its diagnostic accuracy. No standardized criteria are available to assess the quality of CMR studies. We aimed todescribe and validate standardized criteria to evaluate the quality of CMR studies including: a) cine steady-state free precession, b) delayed gadoliniumenhancement, and c) adenosine stress first-pass perfusion. These criteria will serve for the assessment of the image quality in the setting of the Euro-CMR registry.METHOD AND MATERIALS: First, a total of 45 quality criteria were defined (35 qualitative criteria with a score from 0-3, and 10 quantitative criteria). Thequalitative score ranged from 0 to 105. The lower the qualitative score, the better the quality. The quantitative criteria were based on the absolute signal intensity (delayed enhancement) and on the signal increase (perfusion) of the anterior/posterior left ventricular wall after gadolinium injection. These criteria were then applied in 30 patients scanned with a 1.5T system and in 15 patients scanned with a 3.0T system. The examinations were jointly interpreted by 3 CMR experts and 1 study nurse. In these 45 patients the correlation between the results of the quality assessment obtained by the different readers was calculated.RESULTS: On the 1.5T machine, the mean quality score was 3.5. The mean difference between each pair of observers was 0.2 (5.7%) with a mean standarddeviation of 1.4. On the 3.0T machine, the mean quality score was 4.4. The mean difference between each pair of onservers was 0.3 (6.4%) with a meanstandard deviation of 1.6. The quantitative quality assessments between observers were well correlated for the 1.5T machine: R was between 0.78 and 0.99 (pCONCLUSION: The described criteria for the assessment of CMR image quality are robust and have a low inter-observer variability, especially on 1.5T systems.CLINICAL RELEVANCE/APPLICATION: These criteria will allow the standardization of CMR examinations. They will help to improve the overall quality ofexaminations and the comparison between clinical studies.

High-resolution seismic images of potentially seismogenic structures beneath the northwest Canterbury Plains, New Zealand

The transpressional boundary between the Australian and Pacific plates in the central South Island of New Zealand comprises the Alpine Fault and a broad region of distributed strain concentrated in the Southern Alps but encompassing regions further to the east, including the northwest Canterbury Plains. Low to moderate levels of seismicity (e. g., 2 > M 5 events since 1974 and 2 > M 4.0 in 2009) and Holocene sediments offset or disrupted along rare exposed active fault segments are evidence for ongoing tectonism in the northwest plains, the surface topography of which is remarkably flat and even. Because the geology underlying the late Quaternary alluvial fan deposits that carpet most of the plains is not established, the detailed tectonic evolution of this region and the potential for larger earthquakes is only poorly understood. To address these issues, we have processed and interpreted high-resolution (2.5 m subsurface sampling interval) seismic data acquired along lines strategically located relative to extensive rock exposures to the north, west, and southwest and rare exposures to the east. Geological information provided by these rock exposures offer important constraints on the interpretation of the seismic data. The processed seismic reflection sections image a variably thick layer of generally undisturbed younger (i.e., < 24 ka) Quaternary alluvial sediments unconformably overlying an older (> 59 ka) Quaternary sedimentary sequence that shows evidence of moderate faulting and folding during and subsequent to deposition. These Quaternary units are in unconformable contact with Late Cretaceous-Tertiary interbedded sedimentary and volcanic rocks that are highly faulted, folded, and tilted. The lowest imaged unit is largely reflection-free Permian Triassic basement rocks. Quaternary-age deformation has affected all the rocks underlying the younger alluvial sediments, and there is evidence for ongoing deformation. Eight primary and numerous secondary faults as well as a major anticlinal fold are revealed on the seismic sections. Folded sedimentary and volcanic units are observed in the hanging walls and footwalls of most faults. Five of the primary faults represent plausible extensions of mapped faults, three of which are active. The major anticlinal fold is the probable continuation of known active structure. A magnitude 7.1 earthquake occurred on 4 September 2010 near the southeastern edge of our study area. This predominantly right-lateral strike-slip event and numerous aftershocks (ten with magnitudes >= 5 within one week of the main event) highlight the primary message of our paper: that the generally flat and topographically featureless Canterbury Plains is underlain by a network of active faults that have the potential to generate significant earthquakes.