Free-breathing whole-heart coronary MRA with 3D radial SSFP and self-navigated image reconstruction.

Respiratory motion is a major source of artifacts in cardiac magnetic resonance imaging (MRI). Free-breathing techniques with pencil-beam navigators efficiently suppress respiratory motion and minimize the need for patient cooperation. However, the correlation between the measured navigator position and the actual position of the heart may be adversely affected by hysteretic effects, navigator position, and temporal delays between the navigators and the image acquisition. In addition, irregular breathing patterns during navigator-gated scanning may result in low scan efficiency and prolonged scan time. The purpose of this study was to develop and implement a self-navigated, free-breathing, whole-heart 3D coronary MRI technique that would overcome these shortcomings and improve the ease-of-use of coronary MRI. A signal synchronous with respiration was extracted directly from the echoes acquired for imaging, and the motion information was used for retrospective, rigid-body, through-plane motion correction. The images obtained from the self-navigated reconstruction were compared with the results from conventional, prospective, pencil-beam navigator tracking. Image quality was improved in phantom studies using self-navigation, while equivalent results were obtained with both techniques in preliminary in vivo studies.

Image sub-segmentation by PFCM and Artificial Neural Networks to detect pore space in 2D and 3D CT soil images

The image by Computed Tomography is a non-invasive alternative for observing soil structures, mainly pore space. The pore space correspond in soil data to empty or free space in the sense that no material is present there but only fluids, the fluid transport depend of pore spaces in soil, for this reason is important identify the regions that correspond to pore zones. In this paper we present a methodology in order to detect pore space and solid soil based on the synergy of the image processing, pattern recognition and artificial intelligence. The mathematical morphology is an image processing technique used for the purpose of image enhancement. In order to find pixels groups with a similar gray level intensity, or more or less homogeneous groups, a novel image sub-segmentation based on a Possibilistic Fuzzy c-Means (PFCM) clustering algorithm was used. The Artificial Neural Networks (ANNs) are very efficient for demanding large scale and generic pattern recognition applications for this reason finally a classifier based on artificial neural network is applied in order to classify soil images in two classes, pore space and solid soil respectively.

Effect of image analysis software on neurofunctional activation during processing of emotional human faces

Functional brain imaging techniques such as functional MRI (fMRI) that allow the in vivo investigation of the human brain have been exponentially employed to address the neurophysiological substrates of emotional processing. Despite the growing number of fMRI studies in the field, when taken separately these individual imaging studies demonstrate contrasting findings and variable pictures, and are unable to definitively characterize the neural networks underlying each specific emotional condition. Different imaging packages, as well as the statistical approaches for image processing and analysis, probably have a detrimental role by increasing the heterogeneity of findings. In particular, it is unclear to what extent the observed neurofunctional response of the brain cortex during emotional processing depends on the fMRI package used in the analysis. In this pilot study, we performed a double analysis of an fMRI dataset using emotional faces. The Statistical Parametric Mapping (SPM) version 2.6 (Wellcome Department of Cognitive Neurology, London, UK) and the XBAM 3.4 (Brain Imaging Analysis Unit, Institute of Psychiatry, Kings College London, UK) programs, which use parametric and non-parametric analysis, respectively, were used to assess our results. Both packages revealed that processing of emotional faces was associated with an increased activation in the brain`s visual areas (occipital, fusiform and lingual gyri), in the cerebellum, in the parietal cortex, in the cingulate cortex (anterior and posterior cingulate), and in the dorsolateral and ventrolateral prefrontal cortex. However, blood oxygenation level-dependent (BOLD) response in the temporal regions, insula and putamen was evident in the XBAM analysis but not in the SPM analysis. Overall, SPM and XBAM analyses revealed comparable whole-group brain responses. Further Studies are needed to explore the between-group compatibility of the different imaging packages in other cognitive and emotional processing domains. (C) 2009 Elsevier Ltd. All rights reserved.

Three-dimensional space-borne synthetic aperture radar (SAR) imaging with multiple pass processing

Three-dimensional (3D) synthetic aperture radar (SAR) imaging via multiple-pass processing is an extension of interferometric SAR imaging. It exploits more than two flight passes to achieve a desired resolution in elevation. In this paper, a novel approach is developed to reconstruct a 3D space-borne SAR image with multiple-pass processing. It involves image registration, phase correction and elevational imaging. An image model matching is developed for multiple image registration, an eigenvector method is proposed for the phase correction and the elevational imaging is conducted using a Fourier transform or a super-resolution method for enhancement of elevational resolution. 3D SAR images are obtained by processing simulated data and real data from the first European Remote Sensing satellite (ERS-1) with the proposed approaches.

Automatic segmentation and 3D feature extraction of protein aggregates in Caenorhabditis Elegans

In the last years, it has become increasingly clear that neurodegenerative diseases involve protein aggregation, a process often used as disease progression readout and to develop therapeutic strategies. This work presents an image processing tool to automatic segment, classify and quantify these aggregates and the whole 3D body of the nematode Caenorhabditis Elegans. A total of 150 data set images, containing different slices, were captured with a confocal microscope from animals of distinct genetic conditions. Because of the animals’ transparency, most of the slices pixels appeared dark, hampering their body volume direct reconstruction. Therefore, for each data set, all slices were stacked in one single 2D image in order to determine a volume approximation. The gradient of this image was input to an anisotropic diffusion algorithm that uses the Tukey’s biweight as edge-stopping function. The image histogram median of this outcome was used to dynamically determine a thresholding level, which allows the determination of a smoothed exterior contour of the worm and the medial axis of the worm body from thinning its skeleton. Based on this exterior contour diameter and the medial animal axis, random 3D points were then calculated to produce a volume mesh approximation. The protein aggregations were subsequently segmented based on an iso-value and blended with the resulting volume mesh. The results obtained were consistent with qualitative observations in literature, allowing non-biased, reliable and high throughput protein aggregates quantification. This may lead to a significant improvement on neurodegenerative diseases treatment planning and interventions prevention

3D-2D image registration by nonlinear regression

We propose a 3D-2D image registration method that relates image features of 2D projection images to the transformation parameters of the 3D image by nonlinear regression. The method is compared with a conventional registration method based on iterative optimization. For evaluation, simulated X-ray images (DRRs) were generated from coronary artery tree models derived from 3D CTA scans. Registration of nine vessel trees was performed, and the alignment quality was measured by the mean target registration error (mTRE). The regression approach was shown to be slightly less accurate, but much more robust than the method based on an iterative optimization approach.

Development of procedures for the design, optimization and manufacturing of customized orthopaedic and trauma implants: Geometrical/anatomical modelling from 3D medical imaging

Tese de Doutoramento (Programa Doutoral em Engenharia Biomédica)

Does abdominoplasty with liposuction of the love handles yield a shorter scar? An analysis with abdominal 3D laser scanning.

The aim of this study was to evaluate the combination of abdominoplasty with liposuction of both flanks with regards to length of scar, complications, and patient's satisfaction. A retrospective analysis of 35 patients who underwent esthetic abdominoplasty at our institution between 2002 and 2004 was performed. Thirteen patients underwent abdominoplasty with liposuction of both flanks, 22 patients underwent conventional abdominoplasty. Liposuction of the flanks did not increase the rate of complications of the abdominoplasty procedures. We found a tendency toward shorter scars in patients who underwent abdominoplasty combined with liposuction of the flanks. Implementation of 3-dimensional laser surface scanning to objectify the postoperative outcomes, documented a comparable degree of flatness of the achieved body contouring in both procedures. 3-dimensional laser surface scanning can be a valuable tool to objectify assessment of postoperative results.

Superiority of prone position in free-breathing 3D coronary MRA in patients with coronary disease.

Navigator-gated and corrected 3D coronary MR angiography (MRA) allows submillimeter image acquisition during free breathing. However, cranial diaphragmatic drift and relative phase shifts of chest-wall motion are limiting factors for image quality and scanning duration. We hypothesized that image acquisition in the prone position would minimize artifacts related to chest-wall motion and suppress diaphragmatic drift. Twelve patients with radiographically-confirmed coronary artery disease and six healthy adult volunteers were studied in both the prone and the supine position during free-breathing navigator-gated and corrected 3D coronary MRA. Image quality and the diaphragmatic positions were objectively compared. In the prone position, there was a 36% improvement in signal-to-noise ratio (SNR; 15.5 +/- 2.7 vs. 11.4 +/- 2.6; P < 0.01) and a 34% improvement in CNR (12.5 +/- 3.3 vs. 9.3 +/- 2.5, P < 0.01). The prone position also resulted in a 17% improvement in coronary vessel definition (P < 0.01). Cranial end-expiratory diaphragmatic drift occurred less frequently in the prone position (23% +/- 17% vs. 40% +/- 26% supine; P <0.05), and navigator efficiency was higher. Prone coronary MRA results in improved SNR and CNR with enhanced coronary vessel definition. Cranial end-expiratory diaphragmatic drift also was reduced, and navigator efficiency was enhanced. When feasible, prone imaging is recommended for free-breathing coronary MRA.

Online Robust 3D Mapping Using Structure from Motion Cues

This paper presents a complete solution for creating accurate 3D textured models from monocular video sequences. The methods are developed within the framework of sequential structure from motion, where a 3D model of the environment is maintained and updated as new visual information becomes available. The camera position is recovered by directly associating the 3D scene model with local image observations. Compared to standard structure from motion techniques, this approach decreases the error accumulation while increasing the robustness to scene occlusions and feature association failures. The obtained 3D information is used to generate high quality, composite visual maps of the scene (mosaics). The visual maps are used to create texture-mapped, realistic views of the scene

Segmentació de punts 3D rígids i no rígids obtinguts a partir d’un sistema estèreo

L’estudi consta de dues grans parts que serien la part de dissenyar, desenvolupar i implementar els mètodes de segmentació que ens serviran per separar els punts rígids dels punts no rígids/deformables. I l’altra part seria la d’obtenir reconstruccions 3D a partir d’un sistema estèreo, passant per la calibració de les càmeres del sistema, la realització de captures d’experiments reals, la generació de reconstruccions 3D per finalment posar a prova els mètodes desenvolupats en la part anterior

JULIDE: a software tool for 3D reconstruction and statistical analysis of autoradiographic mouse brain sections.

In this article we introduce JULIDE, a software toolkit developed to perform the 3D reconstruction, intensity normalization, volume standardization by 3D image registration and voxel-wise statistical analysis of autoradiographs of mouse brain sections. This software tool has been developed in the open-source ITK software framework and is freely available under a GPL license. The article presents the complete image processing chain from raw data acquisition to 3D statistical group analysis. Results of the group comparison in the context of a study on spatial learning are shown as an illustration of the data that can be obtained with this tool.

Coronary MR imaging using free-breathing 3D steady-state free precession with radial k-space sampling.

PURPOSE: To investigate the potential of free-breathing 3D steady-state free precession (SSFP) imaging with radial k-space sampling for coronary MR-angiography (MRA), coronary projection MR-angiography and coronary vessel wall imaging. MATERIALS AND METHODS: A navigator-gated free-breathing T2-prepared 3D SSFP sequence (TR = 6.1 ms, TE = 3.0 ms, flip angle = 120 degrees, field-of-view = 360 mm(2)) with radial k-space sampling (384 radials) was implemented for coronary MRA. For projection coronary MRA, this sequence was combined with a 2D selective aortic spin tagging pulse. Coronary vessel wall imaging was performed using a high-resolution inversion-recovery black-blood 3D radial SSFP sequence (384 radials, TR = 5.3 ms, TE = 2.7 ms, flip angle = 55 degrees, reconstructed resolution 0.35 x 0.35 x 1.2 mm(3)) and a local re-inversion pulse. Six healthy volunteers (two for each sequence) were investigated. Motion artifact level was assessed by two radiologists. Results: In coronary MRA, the coronary lumen was displayed with a high signal and high contrast to the surrounding lumen. Projection coronary MRA demonstrated selective visualization of the coronary lumen while surrounding tissue was almost completely suppressed. In coronary vessel wall imaging, the vessel wall was displayed with a high signal when compared to the blood pool and the surrounding tissue. No visible motion artifacts were seen. Conclusion: 3D radial SSFP imaging enables coronary MRA, coronary projection MRA and coronary vessel wall imaging with a low motion artifact level.

Positioning an underwater vehicle through image mosaicking

Mosaics have been commonly used as visual maps for undersea exploration and navigation. The position and orientation of an underwater vehicle can be calculated by integrating the apparent motion of the images which form the mosaic. A feature-based mosaicking method is proposed in this paper. The creation of the mosaic is accomplished in four stages: feature selection and matching, detection of points describing the dominant motion, homography computation and mosaic construction. In this work we demonstrate that the use of color and textures as discriminative properties of the image can improve, to a large extent, the accuracy of the constructed mosaic. The system is able to provide 3D metric information concerning the vehicle motion using the knowledge of the intrinsic parameters of the camera while integrating the measurements of an ultrasonic sensor. The experimental results of real images have been tested on the GARBI underwater vehicle