Jaume Garcia-Barnes

A Normalized Framework for the Design of Feature Spaces Assessing the Left Ventricular Function

A through description of the left ventricle functionality requires combining complementary regional scores. A main limitation is the lack of multiparametric normality models oriented to the assessment of regional wall motion abnormalities (RWMA). This paper covers two main topics involved in RWMA assessment. We propose a general framework allowing the fusion and comparison across subjects of different regional scores. Our framework is used to explore which combination of regional scores (including 2-D motion and strains) is better suited for RWMA detection. Our statistical analysis indicates that for a proper (within interobserver variability) identification of RWMA, models should consider motion and extreme strains.

Image-based cardiac phase retrieval in intravascular ultrasound sequences

Longitudinal motion during in vivo pullbacks acquisition of intravascular ultrasound (IVUS) sequences is a major artifact for 3-D exploring of coronary arteries. Most current techniques are based on the electrocardiogram (ECG) signal to obtain a gated pullback without longitudinal motion by using specific hardware or the ECG signal itself. We present an image-based approach for cardiac phase retrieval from coronary IVUS sequences without an ECG signal. A signal reflecting cardiac motion is computed by exploring the image intensity local mean evolution. The signal is filtered by a band-pass filter centered at the main cardiac frequency. Phase is retrieved by computing signal extrema. The average frame processing time using our setup is 36 ms. Comparison to manually sampled sequences encourages a deeper study comparing them to ECG signals.

Manifold parametrization of the left ventricle for a statistical modelling of its complete anatomy

Distortion of Left Ventricle (LV) external anatomy is related to some dysfunctions, such as hypertrophy. The architecture of myocardial fibers determines LV electromechanical activation patterns as well as mechanics. Thus, their joined modelling would allow the design of specific interventions (such as peacemaker implantation and LV remodelling) and therapies (such as resynchronization). On one hand, accurate modelling of external anatomy requires either a dense sampling or a continuous infinite dimensional approach, which requires non-Euclidean statistics. On the other hand, computation of fiber models requires statistics on Riemannian spaces. Most approaches compute separate statistical models for external anatomy and fibers architecture. In this work we propose a general mathematical framework based on differential geometry concepts for computing a statistical model including, both, external and fiber anatomy. Our framework provides a continuous approach to external anatomy supporting standard statistics. We also provide a straightforward formula for the computation of the Riemannian fiber statistics. We have applied our methodology to the computation of complete anatomical atlas of canine hearts from diffusion tensor studies. The orientation of fibers over the average external geometry agrees with the segmental description of orientations reported in the literature.

Adaptation of a computer programming course to the ESHE requirements: evaluation five years later

In the academic year 2010–2011, Spain finished the process of introducing the regulatory changes derived from the Bologna Declaration and the new European Space for Higher Education (ESHE). These changes have implied the updating of university degrees’ structure as well as the inclusion of the European Credit Transfer System (ECTS). This paper describes the process of adaptation of two basic first-semester core subjects of computer engineering to one of the basic aspects of the ESHE, the adoption of the ECTS. The process described in the paper was developed in the framework of the pilot plan undertaken by the Universitat Autònoma de Barcelona between 2005 and 2010. The proposed course design implies a better coordination and integration of the contents of two different subjects that students follow simultaneously, and it is based on the combination of project-based learning and cooperative learning. After the experience finished, an extended quantitative and qualitative analysis of the academic results over the five-year period has shown an improvement in the students’ learning outcomes.

Endowing canonical geometries to cardiac structures

In this paper, we show that canonical (shape-based) geometries can be endowed to cardiac structures using tubular coordinates defined over their medial axis. We give an analytic formulation of these geometries by means of B-Splines. Since B-Splines present vector space structure PCA can be applied to their control points and statistical models relating boundaries and the interior of the anatomical structures can be derived. We demonstrate the applicability in two cardiac structures, the 3D Left Ventricular volume, and the 2D Left-Right ventricle set in 2D Short Axis view.

Decoupled external forces in a predictor-corrector segmentation scheme for LV contours in Tagged MR images

Computation of functional regional scores requires proper identification of LV contours. On one hand, manual segmentation is robust, but it is time consuming and requires high expertise. On the other hand, the tag pattern in TMR sequences is a problem for automatic segmentation of LV boundaries. We propose a segmentation method based on a predictor-corrector (Active Contours - Shape Models) scheme. Special stress is put in the definition of the AC external forces. First, we introduce a semantic description of the LV that discriminates myocardial tissue by using texture and motion descriptors. Second, in order to ensure convergence regardless of the initial contour, the external energy is decoupled according to the orientation of the edges in the image potential. We have validated the model in terms of error in segmented contours and accuracy of regional clinical scores.

Regional motion patterns for the Left Ventricle function assessment

Regional scores (e.g. strain, perfusion) of the Left Ventricle (LV) functionality are playing an increasing role in the diagnosis of cardiac diseases. A main limitation is the lack of normality models for complementary scores oriented to assessment of the LV integrity. This paper introduces an original framework based on a parametrization of the LV domain, which allows comparison across subjects of local physiological measures of different nature. We compute regional normality patterns in a feature space characterizing the LV function. We show the consistency of the model for the regional motion on healthy and hypokinetic pathological cases.

Computation of Left Ventricular Motion Patterns Using a Normalized Parametric Domain

Impairment of left ventricular contractility due to cardiovascular diseases is reflected in the regional motion patterns. Computation of such patterns can help in the detection and localization of any cardiac disorder. In this paper we introduce, a general framework, that we call normalized parametric domain, that allows comparison of vectorial data obtained from several patients. We address both, extraction of the LV motion from tagged magnetic resonance sequences, as well as, defining a mapping of the LV to a common normalized domain. Motion patterns are built from 21 healthy volunteers and correlations with tissue structure is explored.

Influence of the temporal resolution on the quantification of displacement fields in cardiac magnetic resonance tagged images

It is difficult to acquire tagged cardiac MR images with a high temporal and spatial resolution using clinical MR scanners. However, if such images are used for quantifying scores based on motion, it is essential a resolution as high as possible. This paper explores the influence of the temporal resolution of a tagged series on the quantification of myocardial dynamic parameters. To such purpose we have designed a SPAMM (Spatial Modulation of Magnetization) sequence allowing acquisition of sequences at simple and double temporal resolution. Sequences are processed to compute myocardial motion by an automatic technique based on the tracking of the harmonic phase of tagged images (the Harmonic Phase Flow, HPF). The results have been compared to manual tracking of myocardial tags. The error in displacement fields for double resolution sequences reduces 17%.