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).

Debris flow susceptibility mapping at a regional scale along the National Road N7, Argentina

A first assessment of debris flow susceptibility at a large scale was performed along the National Road N7, Argentina. Numerous catchments are prone to debris flows and likely to endanger the road-users. A 1:50,000 susceptibility map was created. The use of a DEM (grid 30 m) associated to three complementary criteria (slope, contributing area, curvature) allowed the identification of potential source areas. The debris flow spreading was estimated using a process- and GISbased model (Flow-R) based on basic probabilistic and energy calculations. The best-fit values for the coefficient of friction and the mass-to-drag ratio of the PCM model were found to be ? = 0.02 and M/D = 180 and the resulting propagation on one of the calibration site was validated using the Coulomb friction model. The results are realistic and will be useful to determine which areas need to be prioritized for detailed studies.

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.

Imaging of tophaceous gout: computed tomography provides specific images compared with magnetic resonance imaging and ultrasonography.

OBJECTIVE: To determine the usefulness of computed tomography (CT), magnetic resonance imaging (MRI), and Doppler ultrasonography (US) in providing specific images of gouty tophi. METHODS: Four male patients with chronic gout with tophi affecting the knee joints (three cases) or the olecranon processes of the elbows (one case) were assessed. Crystallographic analyses of the synovial fluid or tissue aspirates of the areas of interest were made with polarising light microscopy, alizarin red staining, and x ray diffraction. CT was performed with a GE scanner, MR imaging was obtained with a 1.5 T Magneton (Siemens), and ultrasonography with colour Doppler was carried out by standard technique. RESULTS: Crystallographic analyses showed monosodium urate (MSU) crystals in the specimens of the four patients; hydroxyapatite and calcium pyrophosphate dihydrate (CPPD) crystals were not found. A diffuse soft tissue thickening was seen on plain radiographs but no calcifications or ossifications of the tophi. CT disclosed lesions containing round and oval opacities, with a mean density of about 160 Hounsfield units (HU). With MRI, lesions were of low to intermediate signal intensity on T(1) and T(2) weighting. After contrast injection in two cases, enhancement of the tophus was seen in one. Colour Doppler US showed the tophi to be hypoechogenic with peripheral increase of the blood flow in three cases. CONCLUSION: The MR and colour Doppler US images showed the tophi as masses surrounded by a hypervascular area, which cannot be considered as specific for gout. But on CT images, masses of about 160 HU density were clearly seen, which correspond to MSU crystal deposits.