Integrazione di elementi sintetici in scene reali mediante Photoshop 3d e Maya

Lo scopo di questa tesi è dimostrare che è possibile integrare elementi sintetici in scene reali, producendo rendering realistici, avvalendosi di software come Autodesk Maya e Adobe Photoshop. Il progetto, infatti, consiste nella realizzazione di cinque immagini ottenute assemblando in fotografie reali, oggetti 3D, generati usando il software di modellazione Maya, con l’obiettivo di produrre immagini finali altamente fotorealistiche, per cui l’osservatore non riesce a distinguere se l’immagine è reale o sintetica.

Embedding metadata in computer graphics for interaction

Illustration Watermarks, Image annotation, Virtual data exploration, Interaction techniques

Plane-to-plane positioning from image-based visual servoing and structured light

In this paper we face the problem of positioning a camera attached to the end-effector of a robotic manipulator so that it gets parallel to a planar object. Such problem has been treated for a long time in visual servoing. Our approach is based on linking to the camera several laser pointers so that its configuration is aimed to produce a suitable set of visual features. The aim of using structured light is not only for easing the image processing and to allow low-textured objects to be treated, but also for producing a control scheme with nice properties like decoupling, stability, well conditioning and good camera trajectory

Automatic image-based identification of Saimaa ringed seals

The Saimaa ringed seal is one of the most endangered seals in the world. It is a symbol of Lake Saimaa and a lot of effort have been applied to save it. Traditional methods of seal monitoring include capturing the animals and installing sensors on their bodies. These invasive methods for identifying can be painful and affect the behavior of the animals. Automatic identification of seals using computer vision provides a more humane method for the monitoring. This Master's thesis focuses on automatic image-based identification of the Saimaa ringed seals. This consists of detection and segmentation of a seal in an image, analysis of its ring patterns, and identification of the detected seal based on the features of the ring patterns. The proposed algorithm is evaluated with a dataset of 131 individual seals. Based on the experiments with 363 images, 81\% of the images were successfully segmented automatically. Furthermore, a new approach for interactive identification of Saimaa ringed seals is proposed. The results of this research are a starting point for future research in the topic of seal photo-identification.

Plane-to-plane positioning from image-based visual servoing and structured light

In this paper we face the problem of positioning a camera attached to the end-effector of a robotic manipulator so that it gets parallel to a planar object. Such problem has been treated for a long time in visual servoing. Our approach is based on linking to the camera several laser pointers so that its configuration is aimed to produce a suitable set of visual features. The aim of using structured light is not only for easing the image processing and to allow low-textured objects to be treated, but also for producing a control scheme with nice properties like decoupling, stability, well conditioning and good camera trajectory

Single fluoroscopic image based 2D/3D reconstruction of a scaled, patient-specific vertebral model

Purpose Accurate three-dimensional (3D) models of lumbar vertebrae can enable image-based 3D kinematic analysis. The common approach to derive 3D models is by direct segmentation of CT or MRI datasets. However, these have the disadvantages that they are expensive, timeconsuming and/or induce high-radiation doses to the patient. In this study, we present a technique to automatically reconstruct a scaled 3D lumbar vertebral model from a single two-dimensional (2D) lateral fluoroscopic image. Methods Our technique is based on a hybrid 2D/3D deformable registration strategy combining a landmark-to-ray registration with a statistical shape model-based 2D/3D reconstruction scheme. Fig. 1 shows different stages of the reconstruction process. Four cadaveric lumbar spine segments (total twelve lumbar vertebrae) were used to validate the technique. To evaluate the reconstruction accuracy, the surface models reconstructed from the lateral fluoroscopic images were compared to the associated ground truth data derived from a 3D CT-scan reconstruction technique. For each case, a surface-based matching was first used to recover the scale and the rigid transformation between the reconstructed surface model Results Our technique could successfully reconstruct 3D surface models of all twelve vertebrae. After recovering the scale and the rigid transformation between the reconstructed surface models and the ground truth models, the average error of the 2D/3D surface model reconstruction over the twelve lumbar vertebrae was found to be 1.0 mm. The errors of reconstructing surface models of all twelve vertebrae are shown in Fig. 2. It was found that the mean errors of the reconstructed surface models in comparison to their associated ground truths after iterative scaled rigid registrations ranged from 0.7 mm to 1.3 mm and the rootmean squared (RMS) errors ranged from 1.0 mm to 1.7 mm. The average mean reconstruction error was found to be 1.0 mm. Conclusion An accurate, scaled 3D reconstruction of the lumbar vertebra can be obtained from a single lateral fluoroscopic image using a statistical shape model based 2D/3D reconstruction technique. Future work will focus on applying the reconstructed model for 3D kinematic analysis of lumbar vertebrae, an extension of our previously-reported imagebased kinematic analysis. The developed method also has potential applications in surgical planning and navigation.

Mesh-based vs. Image-based Statistical Appearance Model of the Human Femur: a Preliminary Comparison Study for the Creation of Finite Element Meshes

Statistical models have been recently introduced in computational orthopaedics to investigate the bone mechanical properties across several populations. A fundamental aspect for the construction of statistical models concerns the establishment of accurate anatomical correspondences among the objects of the training dataset. Various methods have been proposed to solve this problem such as mesh morphing or image registration algorithms. The objective of this study is to compare a mesh-based and an image-based statistical appearance model approaches for the creation of nite element(FE) meshes. A computer tomography (CT) dataset of 157 human left femurs was used for the comparison. For each approach, 30 finite element meshes were generated with the models. The quality of the obtained FE meshes was evaluated in terms of volume, size and shape of the elements. Results showed that the quality of the meshes obtained with the image-based approach was higher than the quality of the mesh-based approach. Future studies are required to evaluate the impact of this finding on the final mechanical simulations.

Computer-assisted, fluoroscopy-based ventral spondylodesis of thoracolumbar fractures

OBJECTIVE: To design and evaluate a novel computer-assisted, fluoroscopy-based planning and navigation system for minimally invasive ventral spondylodesis of thoracolumbar fractures. MATERIALS AND METHODS: Instruments and an image intensifier are tracked with the SurgiGATE navigation system (Praxim-Medivision). Two fluoroscopic images, one acquired from anterior-posterior (AP) direction and the other from lateral-medial (LM) direction, are used for the complete procedure of planning and navigation. Both of them are calibrated with a custom-made software to recover their projection geometry and to co-register them to a common patient reference coordinate system, which is established by attaching an opto-electronically trackable dynamic reference base (DRB) on the operated vertebra. A bi-planar landmark reconstruction method is used to acquire deep-seated anatomical landmarks such that an intraoperative planning of graft bed can be interactively done. Finally, surgical actions such as the placement of the stabilization devices and the formation of the graft bed using a custom-made chisel are visualized to the surgeon by superimposing virtual instrument representations onto the acquired images. The distance between the instrument tip and each wall of the planned graft bed are calculated on the fly and presented to the surgeon so that the surgeon could formalize the graft bed exactly according to his/her plan. RESULTS: Laboratory studies on phantom and on 27 plastic vertebras demonstrate the high precision of the proposed navigation system. Compared with CT-based measurement, a mean error of 1.0 mm with a standard deviation of 0.1 mm was found. CONCLUSIONS: The proposed computer assisted, fluoroscopy-based planning and navigation system promises to increase the accuracy and reliability of minimally invasive ventral spondylodesis of thoracolumbar fractures.

Non-photorealistic rendering of virtual implant models for computer-assisted fluoroscopy-based surgical procedures

Surgical navigation systems visualize the positions and orientations of surgical instruments and implants as graphical overlays onto a medical image of the operated anatomy on a computer monitor. The orthopaedic surgical navigation systems could be categorized according to the image modalities that are used for the visualization of surgical action. In the so-called CT-based systems or 'surgeon-defined anatomy' based systems, where a 3D volume or surface representation of the operated anatomy could be constructed from the preoperatively acquired tomographic data or through intraoperatively digitized anatomy landmarks, a photorealistic rendering of the surgical action has been identified to greatly improve usability of these navigation systems. However, this may not hold true when the virtual representation of surgical instruments and implants is superimposed onto 2D projection images in a fluoroscopy-based navigation system due to the so-called image occlusion problem. Image occlusion occurs when the field of view of the fluoroscopic image is occupied by the virtual representation of surgical implants or instruments. In these situations, the surgeon may miss part of the image details, even if transparency and/or wire-frame rendering is used. In this paper, we propose to use non-photorealistic rendering to overcome this difficulty. Laboratory testing results on foamed plastic bones during various computer-assisted fluoroscopybased surgical procedures including total hip arthroplasty and long bone fracture reduction and osteosynthesis are shown.

A Survey of Image-based Relighting Techniques

Image-based Relighting (IBRL) has recently attracted a lot of research interest for its ability to relight real objects or scenes, from novel illuminations captured in natural/synthetic environments. Complex lighting effects such as subsurface scattering, interreflection, shadowing, mesostructural self-occlusion, refraction and other relevant phenomena can be generated using IBRL. The main advantage of image-based graphics is that the rendering time is independent of scene complexity as the rendering is actually a process of manipulating image pixels, instead of simulating light transport. The goal of this paper is to provide a complete and systematic overview of the research in Imagebased Relighting. We observe that essentially all IBRL techniques can be broadly classified into three categories (Fig. 9), based on how the scene/illumination information is captured: Reflectance function-based, Basis function-based and Plenoptic function-based. We discuss the characteristics of each of these categories and their representative methods. We also discuss about the sampling density and types of light source(s), relevant issues of IBRL.

An image-based method to automatically propagate bony landmarks: application to computational spine biomechanics.

In attempts to elucidate the underlying mechanisms of spinal injuries and spinal deformities, several experimental and numerical studies have been conducted to understand the biomechanical behavior of the spine. However, numerical biomechanical studies suffer from uncertainties associated with hard- and soft-tissue anatomies. Currently, these parameters are identified manually on each mesh model prior to simulations. The determination of soft connective tissues on finite element meshes can be a tedious procedure, which limits the number of models used in the numerical studies to a few instances. In order to address these limitations, an image-based method for automatic morphing of soft connective tissues has been proposed. Results showed that the proposed method is capable to accurately determine the spatial locations of predetermined bony landmarks. The present method can be used to automatically generate patient-specific models, which may be helpful in designing studies involving a large number of instances and to understand the mechanical behavior of biomechanical structures across a given population.

MR image-based measurement of rates of change in volumes of brain structures. Part 1: Method and validation

A detailed analysis procedure is described for evaluating rates of volumetric change in brain structures based on structural magnetic resonance (MR) images. In this procedure, a series of image processing tools have been employed to address the problems encountered in measuring rates of change based on structural MR images. These tools include an algorithm for intensity non-uniforniity correction, a robust algorithm for three-dimensional image registration with sub-voxel precision and an algorithm for brain tissue segmentation. However, a unique feature in the procedure is the use of a fractional volume model that has been developed to provide a quantitative measure for the partial volume effect. With this model, the fractional constituent tissue volumes are evaluated for voxels at the tissue boundary that manifest partial volume effect, thus allowing tissue boundaries be defined at a sub-voxel level and in an automated fashion. Validation studies are presented on key algorithms including segmentation and registration. An overall assessment of the method is provided through the evaluation of the rates of brain atrophy in a group of normal elderly subjects for which the rate of brain atrophy due to normal aging is predictably small. An application of the method is given in Part 11 where the rates of brain atrophy in various brain regions are studied in relation to normal aging and Alzheimer's disease. (C) 2002 Elsevier Science Inc. All rights reserved.

MR image-based measurement of rates of change in volumes of brain structures. Part II: Application to a study of Alzheimer's disease and normal aging

We present global and regional rates of brain atrophy measured on serially acquired T1-weighted brain MR images for a group of Alzheimer's disease (AD) patients and age-matched normal control (NC) subjects using the analysis procedure described in Part I. Three rates of brain atrophy: the rate of atrophy in the cerebrum, the rate of lateral ventricular enlargement and the rate of atrophy in the region of temporal lobes, were evaluated for 14 AD patients and 14 age-matched NC subjects. All three rates showed significant differences between the two groups, However, the greatest separation of the two groups was obtained when the regional rates were combined. This application has demonstrated that rates of brain atrophy, especially in specific regions of the brain, based on MR images can provide sensitive measures for evaluating the progression of AD. These measures will be useful for the evaluation of therapeutic effects of novel therapies for AD. (C) 2002 Elsevier Science Inc. All rights reserved.