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Morais P.,University of Porto | Queiros S.,University of Minho | Ferreira A.,ICVS 3Bs PT Government Associate Laboratory Braga Guimaraes Portugal | Rodrigues N.F.,Polytechnic Institute of Cavado and Ave | And 4 more authors.
International Journal for Numerical Methods in Biomedical Engineering | Year: 2015

Minimally invasive cardiovascular interventions guided by multiple imaging modalities are rapidly gaining clinical acceptance for the treatment of several cardiovascular diseases. These images are typically fused with richly detailed pre-operative scans through registration techniques, enhancing the intra-operative clinical data and easing the image-guided procedures. Nonetheless, rigid models have been used to align the different modalities, not taking into account the anatomical variations of the cardiac muscle throughout the cardiac cycle. In the current study, we present a novel strategy to compensate the beat-to-beat physiological adaptation of the myocardium. Hereto, we intend to prove that a complete myocardial motion field can be quickly recovered from the displacement field at the myocardial boundaries, therefore being an efficient strategy to locally deform the cardiac muscle. We address this hypothesis by comparing three different strategies to recover a dense myocardial motion field from a sparse one, namely, a diffusion-based approach, thin-plate splines, and multiquadric radial basis functions. Two experimental setups were used to validate the proposed strategy. First, an in silico validation was carried out on synthetic motion fields obtained from two realistic simulated ultrasound sequences. Then, 45 mid-ventricular 2D sequences of cine magnetic resonance imaging were processed to further evaluate the different approaches. The results showed that accurate boundary tracking combined with dense myocardial recovery via interpolation/diffusion is a potentially viable solution to speed up dense myocardial motion field estimation and, consequently, to deform/compensate the myocardial wall throughout the cardiac cycle. © 2015 John Wiley & Sons, Ltd.


Lorintiu O.,INSA Lyon | Liebgott H.,INSA Lyon | Alessandrini M.,Laboratory on Cardiovascular Imaging and Dynamics | Bernard O.,INSA Lyon | Friboulet D.,INSA Lyon
2014 IEEE International Conference on Image Processing, ICIP 2014 | Year: 2014

In this paper we propose a compressed sensing (CS) method adapted to 3D ultrasound imaging (US). In contrast to previous work, we propose a new approach based on the use of learned overcomplete dictionaries. Such dictionaries allow for much sparser representations of the signals since they are optimized for a particular class of images such as US images. We will investigate two undersampling patterns of the 3D US imaging: a spatially uniform random acquisition and a line-wise random acquisition. The latter being extremely interesting for 3D imaging: it would indeed allow skipping the acquisition of many lines among the several thousands required in 3D acquisitions, thus, speeding up the whole acquisition process and incrementing the imaging rate. In this study, the dictionary was learned using the K-SVD algorithm on patches extracted from a training dataset constituted of simulated 3D non-log envelope US volumes. Experiments were performed on a testing dataset made of a simulated 3D US log-envelope volume not included in the testing dataset. CS reconstruction was performed by removing 20% to 80% of the original samples according to the two undersampling patterns. Reconstructions using a K-SVD dictionary previously trained dictionary indicate minimal information loss, thus showing the potential of the overcomplete dictionaries. © 2014 IEEE.


Barbosa D.,Laboratory on Cardiovascular Imaging and Dynamics | Barbosa D.,INSA Lyon | Barbosa D.,Polytechnic Institute of Cavado and Ave | Heyde B.,Laboratory on Cardiovascular Imaging and Dynamics | And 6 more authors.
Computerized Medical Imaging and Graphics | Year: 2014

Image segmentation is an ubiquitous task in medical image analysis, which is required to estimate morphological or functional properties of given anatomical targets. While automatic processing is highly desirable, image segmentation remains to date a supervised process in daily clinical practice. Indeed, challenging data often requires user interaction to capture the required level of anatomical detail. To optimize the analysis of 3D images, the user should be able to efficiently interact with the result of any segmentation algorithm to correct any possible disagreement. Building on a previously developed real-time 3D segmentation algorithm, we propose in the present work an extension towards an interactive application where user information can be used online to steer the segmentation result. This enables a synergistic collaboration between the operator and the underlying segmentation algorithm, thus contributing to higher segmentation accuracy, while keeping total analysis time competitive. To this end, we formalize the user interaction paradigm using a geometrical approach, where the user input is mapped to a non-cartesian space while this information is used to drive the boundary towards the position provided by the user. Additionally, we propose a shape regularization term which improves the interaction with the segmented surface, thereby making the interactive segmentation process less cumbersome. The resulting algorithm offers competitive performance both in terms of segmentation accuracy, as well as in terms of total analysis time. This contributes to a more efficient use of the existing segmentation tools in daily clinical practice. Furthermore, it compares favorably to state-of-the-art interactive segmentation software based on a 3D livewire-based algorithm. © 2013 Elsevier Ltd.


Barbosa D.,Laboratory on Cardiovascular Imaging and Dynamics | Barbosa D.,INSA Lyon | Bernard O.,INSA Lyon | Heyde B.,Laboratory on Cardiovascular Imaging and Dynamics | And 3 more authors.
IEEE International Ultrasonics Symposium, IUS | Year: 2013

Strain-based functional indices have been shown to provide superior performance in assessing global cardiac function when compared with classical volume-based metrics, such as ejection fraction. As in clinical practice global strain is typically used as an index of overall cardiac performance, local tracking algorithms, which are typically computationally intensive, could be substituted by more global approaches. We therefore propose to take advantage of a fast tracking method which uses an optical-flow algorithm on an anatomical ROI to estimate the global cardiac (affine) motion between consecutive frames. The proposed approach was tested in 19 RT3DE exams by assessing the global area strain (GAS), which combines both longitudinal and circumferential deformation. The agreement between the automatic tracking results and the reference show moderate correlation (r=0.698), while Bland-Altman analysis ([μ±1. 96σ]=6.0±9.29%) revealed a significant bias, although having competitive limits of agreement when compared with the inter-observer variability ([μ±1.96σ]=0.85±9.52%). The proposed approach takes less than 1 second to perform the tracking between two subsequent frames, in a MATLAB implementation. These preliminary results point towards the feasibility of online estimation of global deformation parameters without any user intervention and near real-time. © 2013 IEEE.


Barbosa D.,Laboratory on Cardiovascular Imaging and Dynamics | Barbosa D.,University of Lyon | Barbosa D.,INSA Lyon | Heyde B.,Laboratory on Cardiovascular Imaging and Dynamics | And 7 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

Global functional assessment remains a central part of the diagnostic process in daily cardiology practice. Furthermore, real-time 3D echocardiography has been shown to offer superior performance in the assessment of global functional indices, such as stroke volume and ejection fraction, over conventional 2D echo. With this in mind, we present a novel method for tracking the left ventricle (LV) in three-dimensional ultrasound data using a global affine motion model. In order to have a valid region for the underlying assumption of nearly homogeneous motion patterns, we introduce an anatomical region of interest which constrains the global affine motion estimation to a neighborhood around the endocardial surface. This is shown to substantially increase the tracking accuracy and robustness, while simultaneously reducing the required computation time. The proposed anatomical formulation of the optical flow problem is compared with a state-of-the-art real-time tracker and provides competitive performance in the estimation of relevant cardiac volumetric indices used in clinical practice. © 2013 Springer-Verlag.

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