3D reconstruction of ribcage geometry from biplanar radiographs using a statistical parametric model approach

Rib cage 3D reconstruction is an important prerequisite for thoracic spine modelling, particularly for studies of the deformed thorax in adolescent idiopathic scoliosis. This study proposes a new method for rib cage 3D reconstruction from biplanar radiographs, using a statistical parametric model approach. Simplified parametric models were defined at the hierarchical levels of rib cage surface, rib midline and rib surface, and applied on a database of 86 trunks. The resulting parameter database served to statistical models learning which were used to quickly provide a first estimate of the reconstruction from identifications on both radiographs. This solution was then refined by manual adjustments in order to improve the matching between model and image. Accuracy was assessed by comparison with 29 rib cages from CT scans in terms of geometrical parameter differences and in terms of line-to-line error distance between the rib midlines. Intra and inter-observer reproducibility were determined regarding 20 scoliotic patients. The first estimate (mean reconstruction time of 2’30) was sufficient to extract the main rib cage global parameters with a 95% confidence interval lower than 7%, 8%, 2% and 4° for rib cage volume, antero-posterior and lateral maximal diameters and maximal rib hump, respectively. The mean error distance was 5.4 mm (max 35mm) down to 3.6 mm (max 24 mm) after the manual adjustment step (+3’30). The proposed method will improve developments of rib cage finite element modeling and evaluation of clinical outcomes.This work was funded by Paris Tech BiomecAM chair on subject specific muscular skeletal modeling, and we express our acknowledgments to the chair founders: Cotrel foundation, Société générale, Protéor Company and COVEA consortium. We extend your acknowledgements to Alina Badina for medical imaging data, Alexandre Journé for his advices, and Thomas Joubert for his technical support

Decision Support to Crowdsourcing for Annotation and Transcription of Ancient Documents: The RECITAL Workshop

In the 18th century in Paris, only two public theatres could officially perform comedies: the Com{\'e}die-Fran{\c c}aise, and the Com{\'e}die-Italienne. The latter was much less well known. By studying a century of accounting registers, we aim to learn more about its successful plays, its actors, musicians, set designers, and all the small trades necessary for its operation, its administration, logistics and finances. To this end, we employ a mass of untapped and unpublished resources, the 27,544 pages of 63 daily registers available at the Biblioth{\`e}que Nationale de France (BnF). And we take a decidedly fresh look at emerging forms of creation and changes in the entertainmenteconomy. We developed the crowdsourcing platform RECITAL to collect and index the data from theregisters, following an emerging trend in Digital Humanities. RECITAL is built upon the ScribeAPI framework and it offers a fully-fledged web application to classify the pages, annotate with marks and tags, transcribe the indexed marks and even to verify the previous transcripts. We also describe a multi-level data model and to develop a series of monitoring anddecision tools to support crowdsourced data management up to their definitive form

Semi-automated stereoradiographic upper limb 3D reconstructions using a combined parametric and statistical model: a preliminary study

PURPOSE: Quantitative assessment of 3D clinical indices may be crucial for elbow surgery planning. 3D parametric modeling from bi-planar radiographs was successfully proposed for spine and lower limb clinical investigation as an alternative for CT-scan. The aim of this study was to adapt this method to the upper limb with a preliminary validation. METHODS: CT-scan 3D models of humerus, radius and ulna were obtained from 20 cadaveric upper limbs and yielded parametric models made of geometric primitives. Primitives were defined by descriptor parameters (diameters, angles...) and correlations between these descriptors were found. Using these correlations, a semi-automated reconstruction method of humerus using bi-planar radiographs was achieved: a 3D personalized parametric model was built, from which clinical parameters were computed [orientation and projections on bone surface of trochlea sulcus to capitulum (CTS) axis, trochlea sulcus anterior offset and width of distal humeral epiphysis]. This method was evaluated by accuracy compared to CT-scan and reproducibility. RESULTS: Points-to-surface mean distance was 0.9 mm (2 RMS = 2.5 mm). For clinical parameters, mean differences were 0.4-1.9 mm and from 1.7° to 2.3°. All parameters except from angle formed by CTS axis and bi-epicondylar axis in transverse plane were reproducible. Reconstruction time was about 5 min. CONCLUSIONS: The presented method provides access to morphological upper limb parameters with very low level of radiation. Preliminary in vitro validation for humerus showed that it is fast and accurate enough to be used in clinical daily practice as an alternative to CT-scan for total elbow arthroplasty pre operative evaluation

Soft Photon Problem in Leptonic B-decays

We point out at the peculiarity of B --> mu nu decay, namely the enhancement of the soft photon events which originate from the structure dependent part of the B --> mu nu gamma amplitude. This may be a dominant source of systematic uncertainty and compromise the projected experimental uncertainty on Gamma(B --> mu nu). We show that the effect of these soft photons can be controlled if the experimental cut on identification of soft photons is lowered and especially if the better resolution in identifying the momentum of muon emerging from B --> mu nu, is made. A lattice QCD computation of the relevant form factors would be highly helpful for a better numerical control over the structure dependent soft photon emission.Comment: 16 pages, 3 figure

The Impact of Intrinsic Alignments: Cosmological Constraints from a Joint Analysis of Cosmic Shear and Galaxy Survey Data

Constraints on cosmology from recent cosmic shear observations are becoming increasingly sophisticated in their treatment of potential systematic effects. Here we present cosmological constraints which include modelling of intrinsic alignments. We demonstrate how the results are changed for three different intrinsic alignment models, and for two different models of the cosmic shear galaxy population. We find that intrinsic alignments can either reduce or increase measurements of the fluctuation amplitude parameter sigma_8 depending on these decisions, and depending on the cosmic shear survey properties. This is due to the interplay between the two types of intrinsic alignment, II and GI. It has been shown that future surveys must make a careful treatment of intrinsic alignments to avoid significant biases, and that simultaneous constraints from shear-shear and shear-position correlation functions can mitigate the effects. For the first time we here combine constraints from cosmic shear surveys (shear-shear correlations) with those from "GI" intrinsic alignment data sets (shear-position correlations). We produce updated constraints on cosmology marginalised over two free parameters in the halo model for intrinsic alignments. We find that the additional freedom is well compensated by the additional information, in that the constraints are very similar indeed to those obtained when intrinsic alignments are ignored, both in terms of best fit values and uncertainties.Comment: 16 pages, 11 figure