Generating anatomical models of the heart and the aorta from medical images for personalized physiological simulations.

The anatomy and motion of the heart and the aorta are essential for patient-specific simulations of cardiac electrophysiology, wall mechanics and hemodynamics. Within the European integrated project euHeart, algorithms have been developed that allow to efficiently generate patient-specific anatomical models from medical images from multiple imaging modalities. These models, for instance, account for myocardial deformation, cardiac wall motion, and patient-specific tissue information like myocardial scar location. Furthermore, integration of algorithms for anatomy extraction and physiological simulations has been brought forward. Physiological simulations are linked closer to anatomical models by encoding tissue properties, like the muscle fibers, into segmentation meshes. Biophysical constraints are also utilized in combination with image analysis to assess tissue properties. Both examples show directions of how physiological simulations could provide new challenges and stimuli for image analysis research in the future.

Medical informatics and bioinformatics: a bibliometric study.

This paper reports on an analysis of the bioinformatics and medical informatics literature with the objective to identify upcoming trends that are shared among both research fields to derive benefits from potential collaborative initiatives for their future. Our results present the main characteristics of the two fields and show that these domains are still relatively separated.

A new method for PET image reconstruction using Fourier-Wavelet moment.

In this paper, a new non-regularization method for positron emission tomography (PET) reconstruction is proposed. The proposed method is a feature-based method using Fourier-Wavelet basis. In order to obtain the reconstructions, we have to calculate the Fourier-Wavelet moment (FWM) from the measurements. To achieve this, iterative method is employed. The rotation invariance property of the proposed basis permits us to reduce computational cost. A row-action (RA) like fast convergent algorithm is used to further accelerate the convergence rate. In experiment, we compare the proposed method with some existing algorithms. The results show that our method offers good reconstruction quality compared to conventional MAP method.

A grand challenge for research: multimodal, multilevel and multiscale systems in medicine and biology.

Computational modelling, nano-bioscience and information technology in biology and medicine will play a major role in the interdisciplinary attempts to elucidate structures and functions of living systems. Developing tools capable to integrate the new advances and make benefit of them is crucial: accumulation of data and knowledge base with only storage and retrieval capabilities will have a poor impact if they are not made "active" or "operational". This is where models will play a central role in offering, not only sound ways for representation or simulation, but also the appropriate frames to put the players in the right place, with intra- and inter-level coupling and multisource handling. This paper advocated that sequential observations of multiple and complex mechanisms will be of limited interest to understand the inter-relations that are occurring at the same time, and therefore, that designing multimodal, multilevel and multiscale experiments, matched with these models, are of major importance.

A 3D Static Heart Model From a MSCT Data Set.

Dynamic Computed Tomography (CT) imaging aims to access the kinetics of the moving organs. In cardiac imaging, the interest lies in the possibility of obtaining anatomic and functional information on the heart and the coronaries during the same examination. However, segmentation, reconstruction and registration algorithms need to be developed for diagnostic purposes. We propose thus to built a 3D heart model from Multi-slice Spiral Computed Tomography (MSCT) dynamic sequences to facilitate the evaluation of these algorithms. The model building relies on semi-automatic segmentation techniques based on deformable models such as Fast Marching and active contours. Shape-based interpolation and Marching Cube algorithms are then used for the 3D surface reconstruction.

Fast detection and characterization of vessels in very large 3-D data sets using geometrical moments.

An improved and very fast algorithm dealing with the extraction of vessels in three-dimensional imaging is described. The approach is based on geometrical moments and a local cylindrical approximation. A robust estimation of vessel and background intensity levels, position, orientation, and diameter of the vessels with adaptive control of key parameters, is provided during vessel tracking. Experimental results are presented for lower limb arteries in multidetector computed tomography scanner.

Towards dynamic cardiac scenes interpretation based on spatial-temporal knowledge.

Cardiac motion analysis enables to identify pathologies related to myocardial anomalies or coronary arteries circulation deficiencies. Conventionally, bi-dimensional (2D) left ventricle contour images have been extensively used, to perform quantitative measurements and qualitative evaluations of the cardiac function. Nevertheless, there are other cardiac anatomical structures, the coronary arteries, imaged on routine procedures, upon which complementary motion interpretation can be conducted. This paper presents an experimental methodology to perform dynamic cardiac scenes interpretation, studying three-dimensional (3D) coronary arteries spatial-temporal behavior. Being an alternative way to approach computer assisted cardiac motion interpretation, it reveals a wide range of rarely explored spatial-temporal situations and proposes how to address them. Considering the challenges to achieve dynamic scene interpretation, it is explained how spatial and temporal knowledge, are connected to specialist knowledge and measured parameters, to obtain a dynamic scene interpretation. Global and local motion features are modeled according to cardiac motion and geometrical knowledge, before its transformation into symbols. Anatomical knowledge and spatial-temporal knowledge are applied, along with spatial-temporal reasoning schemes, to access symbols meaning. Experimental results obtained using real data are presented. Complexity of interpretation envisioning is discussed, taking the given results as an example.

[The scientific bases of virtual endoscopy]. / Les bases scientifiques de l'endoscopie virtuelle.

The recent advances in medical imaging, the avaibility of methods for image analysis and computer graphics, the technological resources provided by microdevices and the design of minimal access surgical procedures have open the road to new concepts. Virtual endoscopy represents one of these emerging areas and points out the applicative potential of three dimensional (3D) imaging. It leads to less invasive diagnosis and therapeutic achievements and provides important cues for education and interventional planning. Image segmentation, visualization, tissue modeling and interactions with surgical instruments are the fundamental components to build clinical applications. They are examined in this paper through 3D navigation systems, surgical simulations and image guided interventions.

Slice simulation from a model of the parenchymous vascularization to evaluate texture features: work in progress.

RATIONALE AND OBJECTIVES: To demonstrate the usefulness of a model of the parenchymous vascularization to evaluate texture analysis methods. METHODS: Slices with thickness varying from 1 to 4 mm were reformatted from a 3D vascular model corresponding to either normal tissue perfusion or local hypervascularization. Parameters of statistical methods were measured on 16128x128 regions of interest, and mean values and standard deviation were calculated. For each parameter, the performances (discrimination power and stability) were evaluated. RESULTS: Among 11 calculated statistical parameters, three (homogeneity, entropy, mean of gradients) were found to have a good discriminating power to differentiate normal perfusion from hypervascularization, but only the gradient mean was found to have a good stability with respect to the thickness. Five parameters (run percentage, run length distribution, long run emphasis, contrast, and gray level distribution) were found to have intermediate results. In the remaining three, curtosis and correlation was found to have little discrimination power, skewness none. CONCLUSION: This 3D vascular model, which allows the generation of various examples of vascular textures, is a powerful tool to assess the performance of texture analysis methods. This improves our knowledge of the methods and should contribute to their a priori choice when designing clinical studies.

Analysis-synthesis of the phonocardiogram based on the matching pursuit method.

The matching pursuit method of Mallat and Zhang is applied to the analysis and synthesis of phonocardiograms (PCG's). The method is based on a classical Gabor wavelet or time-frequency atom which is the product of a sinusoid and a Gaussian window function. It decomposes a signal into a series of time-frequency atoms by an iterative process based on selecting the largest inner product of the signal (and the subsequent residues) with atoms from a redundant dictionary. The Gaussian window controls the envelope duration and time position of each atom; and the sinusoid represents the frequency. The method was applied to two sets of PCG's: one with very low-noise level and the other with 10% noise energy. Each data base includes 11 PCG's representing the normal and the pathological conditions of the heart. The normalized root-mean-square error (NRMSE) was computed between the original and the reconstructed signals. The results show that the matching pursuit method is very suitable to the transient and complex properties of the PCG's, as it yielded excellent NRMSE's around 2.2% for the two sets of 11 PCG's tested.

Time-frequency scaling transformation of the phonocardiogram based of the matching pursuit method.

A time-frequency scaling transformation based on the matching pursuit (MP) method is developed for the phonocardiogram (PCG). The MP method decomposes a signal into a series of time-frequency atoms by using an iterative process. The modification of the time scale of the PCG can be performed without perceptible change in its spectral characteristics. It is also possible to modify the frequency scale without changing the temporal properties. The technique has been tested on 11 PCG's containing heart sounds and different murmurs. A scaling/inverse-scaling procedure was used for quantitative evaluation of the scaling performance. Both the spectrogram and a MP-based Wigner distribution were used for visual comparison in the time-frequency domain. The results showed that the technique is suitable and effective for the time-frequency scale transformation of both the transient property of the heart sounds and the more complex random property of the murmurs. It is also shown that the effectiveness of the method is strongly related to the optimization of the parameters used for the decomposition of the signals.

Three-dimensional reconstruction of the coronary arteries using a priori knowledge.

A method for 3D reconstruction of the coronary arteries from two radiographic images is presented. A novel technique for matching image structures is the main contribution of the work. After a comprehensive study of the knowledge required to approach this problem, an automatic method, which includes both numeric and symbolic procedures to solve geometric ambiguities, is developed. In the proposed method, all possible (virtual) reconstructions are first obtained. Their validity is evaluated by means of a priori knowledge about the 3D object and its projections. From the set of chosen possible solutions, the most likely solution is selected. The method is tested using real images and is implemented in a platform that allows further clinical validation.

Dynamic feature extraction of coronary artery motion using DSA image sequences.

This paper aims to define and describe features of the motion of coronary arteries in two and three dimensions, presented as geometrical parameters that identify motion patterns. The main left coronary artery centerlines, obtained from digital subtraction angiography (DSA) image sequences, are first reconstructed. Thereafter, global and local motion features are evaluated along the sequence. The global attributes are centerline and point trajectory lengths, displacement amplitude, and virtual reference point, while local attributes are displacement direction, perpendicular/radial components, rotation direction, and curvature and torsion. These kinetic features allow us to obtain a detailed quantitative description of the displacements of arteries' centerlines, as well as associated epicardium deformations. Our modeling of local attributes as quasi-homogeneous on a segment analysis, enables us to propose a novel numeric to symbolic image transformation, which provides the required facts for knowledge-based motion interpretation. Experimental results using real data are consistent with cardiac dynamic behavior.

A method to quantify invariant information in depth-recorded epileptic seizures.

In the field of epilepsy, the analysis of stereoelectroencephalographic (SEEG) signals recorded with depth electrodes provides major information on interactions between brain structures during seizures. A methodology of comparing SEEG seizure recordings is applied in 4 patients suffering from temporal lobe epilepsy. It proceeds in 3 steps: (i) segmentation of SEEG signals, (ii) characterization and labeling of segments and (iii) comparison of observations coded as sequences of symbol vectors. The third step is based on a vectorial extension of Wagner and Fischer's algorithm to first, quantify similarities between observations and second, extract invariant information, referred to as spatio-temporal signatures. These are automatically extracted by the algorithm without the need to make a priori assumptions on the 'patterns' to be searched for. Theoretical results show that two observations of non-equal duration can be matched by deforming the first one (using insertion/deletion operations on vectors) to optimally fit the second, under a minimal cost constraint. Clinical results show that the study brings objective results on reproducible mechanisms occurring during seizures: for a given patient, quantified descriptions of seizure periods are compared and similar ictal patterns, or signatures, are extracted from SEEG signals. Some of these signatures (particularly those containing spikes, spike-and-waves, slow waves and rapid discharges) are relevant: they seem to reflect reproducible propagation schemes whose analysis may help in the understanding of epileptogenic networks.

Biomedical information technology: medicine and health care in the digital future.

Advancements in medicine and health care are being significantly influenced by the exploding information technology developments. The IEEE Transactions on Information Technology in Biomedicine will address the applications and the infrastructure innovations that would harness biomedical and health care programs in the 21st century.

Time-domain quanification of amplitude, chemical shift, apparent relaxation time T2, and phase by wavelet-transform analysis. Application to biomedical magnetic resonance spectroscopy.

The wavelet-transform method is used to quantify the magnetic resonance spectroscopy (MRS) parameters: chemical shift, apparent relaxation time T2, resonance amplitude, and phase. Wavelet transformation is a time-frequency representation which separates each component from the FID, then successively quantifies it and subtracts it from the raw signal. Two iterative procedures have been developed. They have been combined with a nonlinear regression analysis method and tested on both simulated and real sets of biomedical MRS data selected with respect to the main problems usually encountered in quantifying biomedical MRS, specifically "chemical noise," resulting from overlapping resonances, and baseline distortion. The results indicate that the wavelet-transform method can provide efficient and accurate quantification of MRS data.