Piecewise Affine Registration of Biological Images for Volume Reconstruction

This manuscript tackles the reconstruction of 3D volumes via mono-modal registration of series of 2D biological images (histological sections, autoradiographs, cryosections, etc.). The process of acquiring these images typically induces composite transformations that we model as a number of rigid or affine local transformations embedded in an elastic one. We propose a registration approach closely derived from this model. Given a pair of input images, we first compute a dense similarity field between them with a block matching algorithm. We use as a similarity measure an extension of the classical correlation coefficient that improves the consistency of the field. A hierarchical clustering algorithm then automatically partitions the field into a number of classes from which we extract independent pairs of sub-images. Our clustering algorithm relies on the Earth mover’s distribution metric and is additionally guided by robust least-square estimation of the transformations associated with each cluster. Finally, the pairs of sub-images are, independently, affinely registered and a hybrid affine/non-linear interpolation scheme is used to compose the output registered image. We investigate the behavior of our approach on several batches of histological data and discuss its sensitivity to parameters and noise

Mechanical based rigid registration of 3D objects: application to multimodal medical images

The registration of 3-D objects is an important problem in computer vision and especially in medical imaging. It arises when data acquired by different sensors and/or at different times have to be fused. Under the basic assumption that the objects to be registered are rigid, the problem is to recover the six parameters of a rigid transformation. If landmarks or common characteristics are not available, the problem has to be solved by an iterative method . However such methods are inevitably attracted to local minima. This paper presents a novel iterative method designed for the rigid registration of 3-D objects . Its originality lies in its physical basis : instead of minimizing an energy function with respect to the parameters of the rigid transformation (the classical approach) the minimization is achieved by studying the motion of a rigid object in a potential field. In particular we consider the kinetic energy of the solid during the registration process, which allows it to "jump over" some local maxima of the potential energy and so avoid some local minima of that energy. We present extensive experimental results on real 3-D medical images. In that particular application, we perform the matching process with the whole segmented volumes .La mise en correspondance d'objets 3D est un problème important dans le domaine du traitement d'image. Il apparaît lorsque des données acquises par différents capteurs, à des moments ou/et des instants différents doivent être fusionnées. Si l'on suppose que les objets à mettre en correspondance sont rigides, nous avons a retrouver les paramètres d'une transformation rigide. Lorsque l'utilisatin d'amers ou de caractéristiques communes n'est pas possible pour résoudre cette tache, une méthode itérative peut êre utilisée avec profit. Cet article présente une méthode itérative générale pour la mise en correspondance d'objets 3D. Son originalité réside dans ses fondements mecaniques: plutôt que de minimiser une énergie potentielle par rapport aux paramètres de la transformation rigide, qui est l'approche classique, nous étudions le mouvement d'un objet rigide, c'est-à-dire un solide, dans un champ de potentiel. Cette approche particulière prend en compte l'énergie cinétique du solide, ce qui permet de «sauter» certains maxima locaux de l'énergie potentielle et donc d'en éviter certains minima locaux. Nous montrons que notre approche, si l'on considère l'énergie cinétique toujours nulle, est équivalente à une méthode de descente de gradient, l'introduction de la vitesse permet donc d'en accélérer la convergence. En outre, nous montrons que notre méthode se laisse moins facilement «piéger» par les minima locaux de l'énergie que les méthodes classiques de minimisation. L'article est illustré par l'application de la méthode au recalage d'images médicales réelles, ou nous utilisons la totalité du volume segment

Automated Piecewise Affine Registration of Biological Images

This report tackles the registration of 2D biological images (histological sections or autoradiographs) to 2D images from the same or different modalities (e.g., histology or MRI). The process of acquiring these images typically induces composite transformations that we model as a number of rigid or affine local transformations embedded in an elastic one. We propose a registration approach closely derived from this model. Given a pair of input images, we first compute a dense similarity field between them with a block matching algorithm. A hierarchical clustering algorithm then automatically partitions this field into a number of classes from which we extract independent pairs of sub-images. Our clustering algorithm relies on the Earth mover's distribution metric and is additionally guided by robust least-square estimation of the transformations associated with each cluster. Finally, the pairs of sub-images are, independently, affinely registered and a hybrid affine/non-linear interpolation scheme is used to compose the output registered image. We investigate the behavior of our approach under a variety of conditions, and discuss examples using simulated and real medical images, including MRI, autoradiography, histology and cryosection data. We also detail the reconstruction of a 3-D volume from a series of 2-D histological sections and compare it against a reconstruction obtained with a global rigid approach

Characterization of a submicro-X-ray fluorescence setup on the B16 beamline at Diamond Light Source

An X-ray fluorescence setup has been tested on the B16 beamline at the Diamond Light Source synchrotron with two different excitation energies (12.7 and 17 keV). This setup allows the scanning of thin samples (thicknesses up to several micrometers) with a sub-micrometer resolution (beam size of 500 nm × 600 nm determined with a 50 µm Au wire). Sensitivities and detection limits reaching values of 249 counts s−1 fg−1 and 4 ag in 1000 s, respectively (for As Kα excited with 17 keV), are presented in order to demonstrate the capabilities of this setup. Sample measurements of a human bone and a single cell performed at B16 are presented in order to illustrate the suitability of the setup in biological applications.</jats:p

A multiscale analysis of early flower development in Arabidopsis provides an integrated view of molecular regulation and growth control.

We have analyzed the link between the gene regulation and growth during the early stages of flower development in Arabidopsis. Starting from time-lapse images, we generated a 4D atlas of early flower development, including cell lineage, cellular growth rates, and the expression patterns of regulatory genes. This information was introduced in MorphoNet, a web-based platform. Using computational models, we found that the literature-based molecular network only explained a minority of the gene expression patterns. This was substantially improved by adding regulatory hypotheses for individual genes. Correlating growth with the combinatorial expression of multiple regulators led to a set of hypotheses for the action of individual genes in morphogenesis. This identified the central factor LEAFY as a potential regulator of heterogeneous growth, which was supported by quantifying growth patterns in a leafy mutant. By providing an integrated view, this atlas should represent a fundamental step toward mechanistic models of flower development

First Results for the Beam Commissioning of the CERN Multi-Turn Extraction

The Multi-Turn Extraction (MTE), a new type of extraction based on beam trapping inside stable islands in horizontal phase space, has been commissioned during the 2008 run of the CERN Proton Synchrotron. Both singleand multi-bunch beams with a total intensity up to 1.4 1013 protons have been extracted with efficiencies up to 98%. Furthermore, injection tests in the CERN Super Proton Synchrotron were performed, with the beam then accelerated and extracted to produce neutrinos for the CERN Neutrino-to-Gran Sasso experiments. The results of the extensive measurement campaign are presented and discussed in detail

Physical Modelling of the Flow Field in an Undular Tidal Bore

A tidal bore may form in a converging channel with a funnel shape when the tidal range exceeds 6-9 m. The advancing surge has a major impact on the estuarine ecosystem. Physical modelling of an undular bore has been conducted based upon a quasi-steady flow analogy. The experimental data highlight rapid flow redistributions between successive wave troughs and crests as well as large bottom shear stress variations. The results suggest a sediment transport process combining scour beneath wave troughs associated with upward matter dispersion between a trough and the following wave crest. The process is repeated at each trough and significant sediment transport takes place with deposition in upstream intertidal zones. The conceptual model is supported by field observations showing murky waters after the bore passage and long-lasting chaotic waves

Fully automatic anatomical, pathological, and functional segmentation from CT scans for hepatic surgery

International audienceOBJECTIVE: To improve the planning of hepatic surgery, we have developed a fully automatic anatomical, pathological, and functional segmentation of the liver derived from a spiral CT scan. MATERIALS AND METHODS: From a 2 mm-thick enhanced spiral CT scan, the first stage automatically delineates skin, bones, lungs, kidneys, and spleen by combining the use of thresholding, mathematical morphology, and distance maps. Next, a reference 3D model is immersed in the image and automatically deformed to the liver contours. Then an automatic Gaussian fitting on the imaging histogram estimates the intensities of parenchyma, vessels, and lesions. This first result is next improved through an original topological and geometrical analysis, providing an automatic delineation of lesions and veins. Finally, a topological and geometrical analysis based on medical knowledge provides hepatic functional information that is invisible in medical imaging: portal vein labeling and hepatic anatomical segmentation according to the Couinaud classification. RESULTS: Clinical validation performed on more than 30 patients shows that delineation of anatomical structures by this method is often more sensitive and more specific than manual delineation by a radiologist. CONCLUSION: This study describes the methodology used to create the automatic segmentation of the liver with delineation of important anatomical, pathological, and functional structures from a routine CT scan. Using the methods proposed in this study, we have confirmed the accuracy and utility of the creation of a 3D liver model compared with the conventional reading of the CT scan by a radiologist. This work may allow improved preoperative planning of hepatic surgery by more precisely delineating liver pathology and its relationship to normal hepatic structures. In the future, this data may be integrated with computer-assisted surgery and thus represents a first step towards the development of an augmented-reality surgical system