Building and Testing a Statistical Shape Model of the Human Ear Canal

Abstract. Today the design of custom in-the-ear hearing aids is based on personal experience and skills and not on a systematic description of the variation of the shape of the ear canal. In this paper it is described how a dense surface point distribution model of the human ear canal is built based on a training set of laser scanned ear impressions and a sparse set of anatomical landmarks placed by an expert. The landmarks are used to warp a template mesh onto all shapes in the training set. Using the vertices from the warped meshes, a 3D point distribution model is made. The model is used for testing for gender related differences in size and shape of the ear canal.

A Closest Point Proposal for MCMC-based Probabilistic Surface Registration

We propose to view non-rigid surface registration as a probabilistic inference problem. Given a target surface, we estimate the posterior distribution of surface registrations. We demonstrate how the posterior distribution can be used to build shape models that generalize better and show how to visualize the uncertainty in the established correspondence. Furthermore, in a reconstruction task, we show how to estimate the posterior distribution of missing data without assuming a fixed point-to-point correspondence. We introduce the closest-point proposal for the Metropolis-Hastings algorithm. Our proposal overcomes the limitation of slow convergence compared to a random-walk strategy. As the algorithm decouples inference from modeling the posterior using a propose-and-verify scheme, we show how to choose different distance measures for the likelihood model. All presented results are fully reproducible using publicly available data and our open-source implementation of the registration framework

Alternative splicing of the maize Ac transposase transcript in transgenic sugar beet (Beta vulgaris L.)

The maize Activator/Dissociation (Ac/Ds) transposable element system was introduced into sugar beet. The autonomous Ac and non-autonomous Ds element excise from the T-DNA vector and integrate at novel positions in the sugar beet genome. Ac and Ds excisions generate footprints in the donor T-DNA that support the hairpin model for transposon excision. Two complete integration events into genomic sugar beet DNA were obtained by IPCR. Integration of Ac leads to an eight bp duplication, while integration of Ds in a homologue of a sugar beet flowering locus gene did not induce a duplication. The molecular structure of the target site indicates Ds integration into a double strand break. Analyses of transposase transcription using RT–PCR revealed low amounts of alternatively spliced mRNAs. The fourth intron of the transposase was found to be partially misspliced. Four different splice products were identified. In addition, the second and third exon were found to harbour two and three novel introns, respectively. These utilize each the same splice donor but several alternative splice acceptor sites. Using the SplicePredictor online tool, one of the two introns within exon two is predicted to be efficiently spliced in maize. Most interestingly, splicing of this intron together with the four major introns of Ac would generate a transposase that lacks the DNA binding domain and two of its three nuclear localization signals, but still harbours the dimerization domain

Extension of the ICP algorithm to nonrigid intensity-based registration of 3D volumes

We present in this paper a new registration and gain correction algorithm for 3D medical images. It is intensity based. The basic idea is to represent images by 4D points (xj;yj;zj;ij) and to define a global energy function based on this representation. For minimisation, we propose a technique which does not require computing the derivatives of this criterion with respect to the parameters. It can be understood as an extension of the Iterative Closest Point algorithm [5, 56] or as an application of the formalism proposed in [13]. Two parameters enable us to develop a coarse-to-fine strategy both for resolution and for deformation. Our technique presents the advantage of minimising a well-defined global criterion, to deal with various classes of transformations (for example rigid, affine, volume spline and radial basis functions), to be simple to implement, and to be efficient in practice. Results on real brain and heart 3D images are presented to demonstrate the validity of our approach. We also explain how one can compute basic statistics on the deformation parameters to constrain the set of possible deformations by learning and to discriminate between different groups

Spectral fusion for estimating respiratory rate from the ECG

A new method for extracting respiratory signals from the electrocardiogram (ECG) is proposed. The method performs AR spectral analysis on heart rate variability and beat morphology information extracted from the ECG and identifies the closest matched frequencies which then provide an estimate of the respiration frequency. Fusing frequency information from different sources reliably rejects noise and movement-induced artefact and is promising for application to ambulatory hospital data. The performance of the method was validated on two databases of simultaneously recorded ECG and reference respiration signals. The spectral fusion technique is found to correctly estimate respiratory rate 90% of the time in the case of non-ambulatory data and 86% of the time in the case of ambulatory data with a root mean square error of 0.92 and 1.40 breaths per minute, respectively. ©2009 IEEE

Using rigid motion constraints for the registration of free-form surfaces

We present a new method for registration of free-form surfaces based on the iterative closest point (ICP) method and on geometric properties of reflected correspondence vectors. The method is based on computing relative gaps between reflected correspondences and between the projections of reflected correspondences along the rotation axis and using these to eliminate false matches. Experimental results on synthetic data and on real range images demonstrate that the method is robust and accurate for image registration with small motions. Copyright (C) 2001 by W.B. Saunders Company

Automated LV motion analysis from 3D echocardiography

3D-cardiac analysis methods based on MRI, CT and nuclear imaging techniques are being developed which begin to elucidate the relationship between 3D shape deformation and heart malfunction. However, recent advances in 3D+T cardiac ultrasound (US) acquisition technology potentially offer now a near-real-time, noninvasive alternative to these methods, at a moderate cost. In this paper we describe an approach to left ventricular (LV) reconstruction and motion analysis, as a first step towards rapid quantification of regional heart performance based on 3D-US. We outline an automated approach that combines state-of-the-art 2D-echogram feature detection with 3D-reconstruction and shape-modelling methods that are being developed for taggedMRI and SPECT cardiac imagery. We evaluate our approach on 3D+T dense and simulated free-hand sparse images. Results on real cardiac and phantom data are presented in a qualitative and quantitative manner