An active contour-based atlas registration model applied to automatic subthalamic nucleus targeting on MRI: method and validation.

This paper presents a new non parametric atlas registration framework, derived from the optical flow model and the active contour theory, applied to automatic subthalamic nucleus (STN) targeting in deep brain stimulation (DBS) surgery. In a previous work, we demonstrated that the STN position can be predicted based on the position of surrounding visible structures, namely the lateral and third ventricles. A STN targeting process can thus be obtained by registering these structures of interest between a brain atlas and the patient image. Here we aim to improve the results of the state of the art targeting methods and at the same time to reduce the computational time. Our simultaneous segmentation and registration model shows mean STN localization errors statistically similar to the most performing registration algorithms tested so far and to the targeting expert's variability. Moreover, the computational time of our registration method is much lower, which is a worthwhile improvement from a clinical point of view.

Active Contour-Based Segmentation of Head and Neck with Adaptive Atlas Selection

This paper presents automated segmentation of structuresin the Head and Neck (H\&N) region, using an activecontour-based joint registration and segmentation model.A new atlas selection strategy is also used. Segmentationis performed based on the dense deformation fieldcomputed from the registration of selected structures inthe atlas image that have distinct boundaries, onto thepatient's image. This approach results in robustsegmentation of the structures of interest, even in thepresence of tumors, or anatomical differences between theatlas and the patient image. For each patient, an atlasimage is selected from the available atlas-database,based on the similarity metric value, computed afterperforming an affine registration between each image inthe atlas-database and the patient's image. Unlike manyof the previous approaches in the literature, thesimilarity metric is not computed over the entire imageregion; rather, it is computed only in the regions ofsoft tissue structures to be segmented. Qualitative andquantitative evaluation of the results is presented.

The Escherichia coli RuvB branch migration protein forms double hexameric rings around DNA.

The RuvB protein is induced in Escherichia coli as part of the SOS response to DNA damage. It is required for genetic recombination and the postreplication repair of DNA. In vitro, the RuvB protein promotes the branch migration of Holliday junctions and has a DNA helicase activity in reactions that require ATP hydrolysis. We have used electron microscopy, image analysis, and three-dimensional reconstruction to show that the RuvB protein, in the presence of ATP, forms a dodecamer on double-stranded DNA in which two stacked hexameric rings encircle the DNA and are oriented in opposite directions with D6 symmetry. Although helicases are ubiquitous and essential for many aspects of DNA repair, replication, and transcription, three-dimensional reconstruction of a helicase has not yet been reported, to our knowledge. The structural arrangement that is seen may be common to other helicases, such as the simian virus 40 large tumor antigen.

Direct three-dimensional myocardial strain tensor quantification and tracking using zHARP.

Images of myocardial strain can be used to diagnose heart disease, plan and monitor treatment, and to learn about cardiac structure and function. Three-dimensional (3D) strain is typically quantified using many magnetic resonance (MR) images obtained in two or three orthogonal planes. Problems with this approach include long scan times, image misregistration, and through-plane motion. This article presents a novel method for calculating cardiac 3D strain using a stack of two or more images acquired in only one orientation. The zHARP pulse sequence encodes in-plane motion using MR tagging and out-of-plane motion using phase encoding, and has been previously shown to be capable of computing 3D displacement within a single image plane. Here, data from two adjacent image planes are combined to yield a 3D strain tensor at each pixel; stacks of zHARP images can be used to derive stacked arrays of 3D strain tensors without imaging multiple orientations and without numerical interpolation. The performance and accuracy of the method is demonstrated in vitro on a phantom and in vivo in four healthy adult human subjects.

Efficient total variation algorithm for fetal brain MRI reconstruction.

Fetal MRI reconstruction aims at finding a high-resolution image given a small set of low-resolution images. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has considered several regularization terms s.a. Dirichlet/Laplacian energy, Total Variation (TV)- based energies and more recently non-local means. Although TV energies are quite attractive because of their ability in edge preservation, standard explicit steepest gradient techniques have been applied to optimize fetal-based TV energies. The main contribution of this work lies in the introduction of a well-posed TV algorithm from the point of view of convex optimization. Specifically, our proposed TV optimization algorithm or fetal reconstruction is optimal w.r.t. the asymptotic and iterative convergence speeds O(1/n2) and O(1/√ε), while existing techniques are in O(1/n2) and O(1/√ε). We apply our algorithm to (1) clinical newborn data, considered as ground truth, and (2) clinical fetal acquisitions. Our algorithm compares favorably with the literature in terms of speed and accuracy.

Mental imagery for full and upper human bodies: common right hemisphere activations and distinct extrastriate activations.

The processing of human bodies is important in social life and for the recognition of another person's actions, moods, and intentions. Recent neuroimaging studies on mental imagery of human body parts suggest that the left hemisphere is dominant in body processing. However, studies on mental imagery of full human bodies reported stronger right hemisphere or bilateral activations. Here, we measured functional magnetic resonance imaging during mental imagery of bilateral partial (upper) and full bodies. Results show that, independently of whether a full or upper body is processed, the right hemisphere (temporo-parietal cortex, anterior parietal cortex, premotor cortex, bilateral superior parietal cortex) is mainly involved in mental imagery of full or partial human bodies. However, distinct activations were found in extrastriate cortex for partial bodies (right fusiform face area) and full bodies (left extrastriate body area). We propose that a common brain network, mainly on the right side, is involved in the mental imagery of human bodies, while two distinct brain areas in extrastriate cortex code for mental imagery of full and upper bodies.

Accuracy and predictability in use of AO three-dimensionally preformed titanium mesh plates for posttraumatic orbital reconstruction: a pilot study.

The aim of this study was to prospectively evaluate the accuracy and predictability of new three-dimensionally preformed AO titanium mesh plates for posttraumatic orbital wall reconstruction.We analyzed the preoperative and postoperative clinical and radiologic data of 10 patients with isolated blow-out orbital fractures. Fracture locations were as follows: floor (N = 7; 70%), medial wall (N = 1; 1%), and floor/medial wall (N = 2; 2%). The floor fractures were exposed by a standard transconjunctival approach, whereas a combined transcaruncular transconjunctival approach was used in patients with medial wall fractures. A three-dimensional preformed AO titanium mesh plate (0.4 mm in thickness) was selected according to the size of the defect previously measured on the preoperative computed tomographic (CT) scan examination and fixed at the inferior orbital rim with 1 or 2 screws. The accuracy of plate positioning of the reconstructed orbit was assessed on the postoperative CT scan. Coronal CT scan slices were used to measure bony orbital volume using OsiriX Medical Image software. Reconstructed versus uninjured orbital volume were statistically correlated.Nine patients (90%) had a successful treatment outcome without complications. One patient (10%) developed a mechanical limitation of upward gaze with a resulting handicapping diplopia requiring hardware removal. Postoperative orbital CT scan showed an anatomic three-dimensional placement of the orbital mesh plates in all of the patients. Volume data of the reconstructed orbit fitted that of the contralateral uninjured orbit with accuracy to within 2.5 cm(3). There was no significant difference in volume between the reconstructed and uninjured orbits.This preliminary study has demonstrated that three-dimensionally preformed AO titanium mesh plates for posttraumatic orbital wall reconstruction results in (1) a high rate of success with an acceptable rate of major clinical complications (10%) and (2) an anatomic restoration of the bony orbital contour and volume that closely approximates that of the contralateral uninjured orbit.

Measuring the diurnal pattern of leaf hyponasty and growth in Arabidopsis - a novel phenotyping approach using laser scanning

Plants forming a rosette during their juvenile growth phase, such as Arabidopsis thaliana (L.) Heynh., are able to adjust the size, position and orientation of their leaves. These growth responses are under the control of the plants circadian clock and follow a characteristic diurnal rhythm. For instance, increased leaf elongation and hyponasty - defined here as the increase in leaf elevation angle - can be observed when plants are shaded. Shading can either be caused by a decrease in the fluence rate of photosynthetically active radiation (direct shade) or a decrease in the fluence rate of red compared with far-red radiation (neighbour detection). In this paper we report on a phenotyping approach based on laser scanning to measure the diurnal pattern of leaf hyponasty and increase in rosette size. In short days, leaves showed constitutively increased leaf elevation angles compared with long days, but the overall diurnal pattern and the magnitude of up and downward leaf movement was independent of daylength. Shade treatment led to elevated leaf angles during the first day of application, but did not affect the magnitude of up and downward leaf movement in the following day. Using our phenotyping device, individual plants can be non-invasively monitored during several days under different light conditions. Hence, it represents a proper tool to phenotype light- and circadian clock-mediated growth responses in order to better understand the underlying regulatory genetic network.

Reconfigurable Architecture To Estimate The Motion Of An Underwater Vehicle

This work proposes a parallel architecture for a motion estimation algorithm. It is well known that image processing requires a huge amount of computation, mainly at low level processing where the algorithms are dealing with a great numbers of data-pixel. One of the solutions to estimate motions involves detection of the correspondences between two images. Due to its regular processing scheme, parallel implementation of correspondence problem can be an adequate approach to reduce the computation time. This work introduces parallel and real-time implementation of such low-level tasks to be carried out from the moment that the current image is acquired by the camera until the pairs of point-matchings are detected

Apport du CT-3D dans le diagnostic et le traitement des fractures des plateaux tibiaux [Value of 3D CT in diagnosis and treatment of fractures of the tibial plateau]

A precise classification and an optimal understanding of tibial plateau fractures are the basis of a conservative treatment or adequate surgery. The aim of this prospective study is to determine the contribution of 3D CT to the classification of fractures (comparison with standard X-rays) and as an aid to the surgeon in preoperative planning and surgical reconstruction. Between November 1994 and July 1996, 20 patients presenting 22 tibial plateau fractures were considered in this study. They all underwent surgical treatment. The fractures were classified according to the Müller AO classification. They were all investigated by means of standard X-rays (AP, profile, oblique) and the 3D CT. Analysis of the results has shown the superiority of 3D CT in the planning (easier and more acute), in the classification (more precise), and in the exact assessment of the lesions (quantity of fragments); thereby proving to be of undeniable value of the surgeon.

Surface reconstruction from microscopic images in optical lithography.

This paper presents a method to reconstruct 3D surfaces of silicon wafers from 2D images of printed circuits taken with a scanning electron microscope. Our reconstruction method combines the physical model of the optical acquisition system with prior knowledge about the shapes of the patterns in the circuit; the result is a shape-from-shading technique with a shape prior. The reconstruction of the surface is formulated as an optimization problem with an objective functional that combines a data-fidelity term on the microscopic image with two prior terms on the surface. The data term models the acquisition system through the irradiance equation characteristic of the microscope; the first prior is a smoothness penalty on the reconstructed surface, and the second prior constrains the shape of the surface to agree with the expected shape of the pattern in the circuit. In order to account for the variability of the manufacturing process, this second prior includes a deformation field that allows a nonlinear elastic deformation between the expected pattern and the reconstructed surface. As a result, the minimization problem has two unknowns, and the reconstruction method provides two outputs: 1) a reconstructed surface and 2) a deformation field. The reconstructed surface is derived from the shading observed in the image and the prior knowledge about the pattern in the circuit, while the deformation field produces a mapping between the expected shape and the reconstructed surface that provides a measure of deviation between the circuit design models and the real manufacturing process.

Can MRI replace CT in evaluating semicircular canal dehiscence?

BACKGROUND AND PURPOSE: Patients with symptoms of semicircular canal dehiscence often undergo both CT and MR imaging. We assessed whether FIESTA can replace temporal bone CT in evaluating patients for SC dehiscence. MATERIALS AND METHODS: We retrospectively reviewed 112 consecutive patients (224 ears) with vestibulocochlear symptoms who underwent concurrent MR imaging and CT of the temporal bones between 2007 and 2009. MR imaging protocol included a FIESTA sequence covering the temporal bone (axial 0.8-mm section thickness, 0.4-mm spacing, coronal/oblique reformations; 41 patients at 1.5T, 71 patients at 3T). CT was performed on a 64-row multidetector row scanner (0.625-mm axial acquisition, with coronal/oblique reformations). Both ears of each patient were evaluated for dehiscence of the superior and posterior semicircular canals in consensual fashion by 2 neuroradiologists. Analysis of the FIESTA sequence and reformations was performed first for the MR imaging evaluation. CT evaluation was performed at least 2 weeks after the MR imaging review, resulting in a blinded comparison of CT with MR imaging. CT was used as the reference standard to evaluate the MR imaging results. RESULTS: For SSC dehiscence, MR imaging sensitivity was 100%, specificity was 96.5%, positive predictive value was 61.1%, and negative predictive value was 100% in comparison with CT. For PSC dehiscence, MR imaging sensitivity was 100%, specificity was 99.1%, positive predictive value was 33.3%, and negative predictive value was 100% in comparison with CT. CONCLUSIONS: MR imaging, with a sensitivity and negative predictive value of 100%, conclusively excludes SSC or PSC dehiscence. Negative findings on MR imaging preclude the need for CT to detect SC dehiscence. Only patients with positive findings on MR imaging should undergo CT evaluation.

Kernel-based Mapping of Meteorological Fields in Complex Orography

Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.