3D Frangi-based lung vessel enhancement filter penalizing airways

This paper describes a fully automatic simultaneous lung vessel and airway enhancement filter. The approach consists of a Frangi-based multiscale vessel enhancement filtering specifically designed for lung vessel and airway detection, where arteries and veins have high contrast with respect to the lung parenchyma, and airway walls are hollow tubular structures with a non negative response using the classical Frangi's filter. The features extracted from the Hessian matrix are used to detect centerlines and approximate walls of airways, decreasing the filter response in those areas by applying a penalty function to the vesselness measure. We validate the segmentation method in 20 CT scans with different pathological states within the VESSEL12 challenge framework. Results indicate that our approach obtains good results, decreasing the number of false positives in airway walls.

Identification of pore spaces in 3D CT soil images using a PFCM partitional clustering

Recent advances in non-destructive imaging techniques, such as X-ray computed tomography (CT), make it possible to analyse pore space features from the direct visualisation from soil structures. A quantitative characterisation of the three-dimensional solid-pore architecture is important to understand soil mechanics, as they relate to the control of biological, chemical, and physical processes across scales. This analysis technique therefore offers an opportunity to better interpret soil strata, as new and relevant information can be obtained. In this work, we propose an approach to automatically identify the pore structure of a set of 200-2D images that represent slices of an original 3D CT image of a soil sample, which can be accomplished through non-linear enhancement of the pixel grey levels and an image segmentation based on a PFCM (Possibilistic Fuzzy C-Means) algorithm. Once the solids and pore spaces have been identified, the set of 200-2D images is then used to reconstruct an approximation of the soil sample by projecting only the pore spaces. This reconstruction shows the structure of the soil and its pores, which become more bounded, less bounded, or unbounded with changes in depth. If the soil sample image quality is sufficiently favourable in terms of contrast, noise and sharpness, the pore identification is less complicated, and the PFCM clustering algorithm can be used without additional processing; otherwise, images require pre-processing before using this algorithm. Promising results were obtained with four soil samples, the first of which was used to show the algorithm validity and the additional three were used to demonstrate the robustness of our proposal. The methodology we present here can better detect the solid soil and pore spaces on CT images, enabling the generation of better 2D?3D representations of pore structures from segmented 2D images.

Anastigmatic imaging with unconstrained object to image mapping

Anastigmatic imaging of an object to an image surfaces without the point-to-point mapping prescription and using a single optical surface is analyzed in 2D and 3D geometries (free-form and rotational-symmetric). Several design techniques are shown.

Basement structure of the Hontomín CO2 storage site (Spain) determined by integration of microgravity and 3D seismic data

We dedicate this paper to the memory of Prof. Andres Perez Estaún, who was a great and committed scientist, wonderful colleague and even better friend. The datasets in this work have been funded by Fundación Ciudad de la Energía (Spanish Government, www.ciuden.es) and by the European Union through the “European Energy Programme 15 for Recovery” and the Compostilla OXYCFB300 project. Dr. Juan Alcalde is currently funded by NERC grant NE/M007251/1. Simon Campbell and Samuel Cheyney are acknowledged for thoughtful comments on gravity inversion

3D Visual Data-Driven Spatiotemporal Deformations for Non-Rigid Object Grasping Using Robot Hands

Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object’s surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand’s fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor environments.

Susac's syndrome: Leptomeningeal enhancement on 3D FLAIR MRI

BACKGROUND Contrast-enhanced (ce) fluid-attenuated inversion recovery magnetic resonance imaging (FLAIR MRI) has recently been shown to identify leptomeningeal pathology in multiple sclerosis. OBJECTIVE To demonstrate leptomeningeal enhancement on three-dimensional (3D) FLAIR in a case of Susac's syndrome. METHODS Leptomeningeal enhancement was correlated with clinical activity over 20 months and compared to retinal fluorescein angiography. RESULTS The size, number, and location of leptomeningeal enhancement varied over time and generally correlated with symptom severity. The appearance was remarkably similar to that of retinal vasculopathy. CONCLUSION Ce 3D FLAIR may aid in diagnosis and understanding of pathophysiology in Susac's syndrome and may serve as a biomarker for disease activity.

A novel phantom and method for comprehensive 3-dimensional measurement and correction of geometric distortion in magnetic resonance imaging

A phantom that can be used for mapping geometric distortion in magnetic resonance imaging (MRI) is described. This phantom provides an array of densely distributed control points in three-dimensional (3D) space. These points form the basis of a comprehensive measurement method to correct for geometric distortion in MR images arising principally from gradient field non-linearity and magnet field inhomogeneity. The phantom was designed based on the concept that a point in space can be defined using three orthogonal planes. This novel design approach allows for as many control points as desired. Employing this novel design, a highly accurate method has been developed that enables the positions of the control points to be measured to sub-voxel accuracy. The phantom described in this paper was constructed to fit into a body coil of a MRI scanner, (external dimensions of the phantom were: 310 mm x 310 mm x 310 mm), and it contained 10,830 control points. With this phantom, the mean errors in the measured coordinates of the control points were on the order of 0.1 mm or less, which were less than one tenth of the voxel's dimensions of the phantom image. The calculated three-dimensional distortion map, i.e., the differences between the image positions and true positions of the control points, can then be used to compensate for geometric distortion for a full image restoration. It is anticipated that this novel method will have an impact on the applicability of MRI in both clinical and research settings. especially in areas where geometric accuracy is highly required, such as in MR neuro-imaging. (C) 2004 Elsevier Inc. All rights reserved.

Geometric distortion in clinical MRI systems - Part II: correction using a 3D phantom

In this paper, we present the correction of the geometric distortion measured in the clinical magnetic resonance imaging (MRI) systems reported in the preceding paper (Part 1) using a 3D method based on the phantom-mapped geometric distortion data. This method allows the correction to be made on phantom images acquired without or with the vendor correction applied. With the vendor's 2D correction applied, the method corrects for both the residual geometric distortion still present in the plane in which the correction method was applied (the axial plane) and the uncorrected geometric distortion along the axis non-nal to the plane. The evaluation of the effectiveness of the correction using this new method was carried out through analyzing the residual geometric distortion in the corrected phantom images. The results show that the new method can restore the distorted images in 3D nearly to perfection. For all the MRI systems investigated, the mean absolute deviations in the positions of the control points (along x-, y- and z-axes) measured on the corrected phantom images were all less than 0.2 mm. The maximum absolute deviations were all below similar to0.8 mm. As expected, the correction of the phantom images acquired with the vendor's correction applied in the axial plane performed equally well. Both the geometric distortion still present in the axial plane after applying the vendor's correction and the uncorrected distortion along the z-axis have all been restored. (C) 2004 Elsevier Inc. All rights reserved.

Geometric distortion in clinical MRI systems - Part I: evaluation using a 3D phantom

Recently, a 3D phantom that can provide a comprehensive and accurate measurement of the geometric distortion in MRI has been developed. Using this phantom, a full assessment of the geometric distortion in a number of clinical MRI systems (GE and Siemens) has been carried out and detailed results are presented in this paper. As expected, the main source of geometric distortion in modern superconducting MRI systems arises from the gradient field nonlinearity. Significantly large distortions with maximum absolute geometric errors ranged between 10 and 25 mm within a volume of 240 x 240 x 240 mm(3) were observed when imaging with the new generation of gradient systems that employs shorter coils. By comparison, the geometric distortion was much less in the older-generation gradient systems. With the vendor's correction method, the geometric distortion measured was significantly reduced but only within the plane in which these 2D correction methods were applied. Distortion along the axis normal to the plane was, as expected, virtually unchanged. Two-dimensional correction methods are a convenient approach and in principle they are the only methods that can be applied to correct geometric distortion in a single slice or in multiple noncontiguous slices. However, these methods only provide an incomplete solution to the problem and their value can be significantly reduced if the distortion along the normal of the correction plane is not small. (C) 2004 Elsevier Inc. All rights reserved.

NMR imaging of the diffusion of water at 310 K into poly[(2-hydroxyethyl methacrylate)-co-(tetrahydrofurfuryl methacrylate)] containing vitamin B12 or aspirin

The ingress of water into copolymers of 2-hydroxyethyl methacrylate (HEMA) and tetrahydrofurfuryl methacrylate (THFMA) loaded with either one of two model drugs, ie vitamin B-12 or aspirin, was studied at 310 K using three-dimensional nuclear magnetic resonance (3D NMR) imaging. The poly(HEMA) was loaded with 5 wt% of the drugs. From the imaging profiles it was observed that incorporation of vitamin B-12 into the polymers rich in HEMA resulted in crack formation at the interface between the rubbery region and the glassy core on sorption of water, although these cracks were 'healed' behind the diffusion front. However, for the copolymers with low HEMA contents and for those containing aspirin, no evidence for similar crack formation was found. For the copolymers loaded with 5 wt% of aspirin or vitamin B-12 the values of the water diffusion coefficients, determined by curve-fitting the relative water concentration profiles from magnetic resonance imaging (MRI) measurements, were found to be smaller than those obtained from a mass uptake study. (C) 2004 Society of Chemical Industry.

Comparison between real-time three-dimensional echocardiography, T1-201 single photon emission computed tomography and cardiac magnetic resonance imaging in the quantitative assessment of left ventricular volumes

Left ventricular (LV) volumes have important prognostic implications in patients with chronic ischemic heart disease. We sought to examine the accuracy and reproducibility of real-time 3D echo (RT-3DE) compared to TI-201 single photon emission computed tomography (SPECT) and cardiac magnetic resonance imaging (MRI). Thirty (n = 30) patients (age 62±9 years, 23 men) with chronic ischemic heart disease underwent LV volume assessment with RT-3DE, SPECT, and MRI. Ano vel semi-automated border detection algorithmwas used by RT-3DE. End diastolic volumes (EDV) and end systolic volumes (ESV) measured by RT3DE and SPECT were compared to MRI as the standard of reference. RT-3DE and SPECT volumes showed excellent correlation with MRI (Table). Both RT- 3DE and SPECT underestimated LV volumes compared to MRI (ESV, SPECT 74±58 ml versus RT-3DE 95±48 ml versus MRI 96±54 ml); (EDV, SPECT 121±61 ml versus RT-3DE 169±61 ml versus MRI 179±56 ml). The degree of ESV underestimation with RT-3DE was not significant.

Automatic initialisation of 3D deformable models for cartilage segmentation

Deformable models are a highly accurate and flexible approach to segmenting structures in medical images. The primary drawback of deformable models is that they are sensitive to initialisation, with accurate and robust results often requiring initialisation close to the true object in the image. Automatically obtaining a good initialisation is problematic for many structures in the body. The cartilages of the knee are a thin elastic material that cover the ends of the bone, absorbing shock and allowing smooth movement. The degeneration of these cartilages characterize the progression of osteoarthritis. The state of the art in the segmentation of the cartilage are 2D semi-automated algorithms. These algorithms require significant time and supervison by a clinical expert, so the development of an automatic segmentation algorithm for the cartilages is an important clinical goal. In this paper we present an approach towards this goal that allows us to automatically providing a good initialisation for deformable models of the patella cartilage, by utilising the strong spatial relationship of the cartilage to the underlying bone.

3D information visualisation: An historical perspective

The use of 3D visualisation of digital information is a recent phenomenon. It relies on users understanding 3D perspectival spaces. Questions about the universal access of such spaces has been debated since its inception in the European Renaissance. Perspective has since become a strong cultural influence in Western visual communication. Perspective imaging assists the process of experimenting by the sketching or modelling of ideas. In particular, the recent 3D modelling of an essentially non-dimensional Cyber-space raises questions of how we think about information in general. While alternate methods clearly exist they are rarely explored within the 3D paradigm (such as Chinese isometry). This paper seeks to generate further discussion on the historical background of perspective and its role in underpinning this emergent field. © 2005 IEEE.

3D statistical shape models to embed spatial relationship information

This paper presents the creation of 3D statistical shape models of the knee bones and their use to embed information into a segmentation system for MRIs of the knee. We propose utilising the strong spatial relationship between the cartilages and the bones in the knee by embedding this information into the created models. This information can then be used to automate the initialisation of segmentation algorithms for the cartilages. The approach used to automatically generate the 3D statistical shape models of the bones is based on the point distribution model optimisation framework of Davies. Our implementation of this scheme uses a parameterized surface extraction algorithm, which is used as the basis for the optimisation scheme that automatically creates the 3D statistical shape models. The current approach is illustrated by generating 3D statistical shape models of the patella, tibia and femoral bones from a segmented database of the knee. The use of these models to embed spatial relationship information to aid in the automation of segmentation algorithms for the cartilages is then illustrated.