Add-on in blender per la deformazione di mesh poligonali

L’idea da cui nasce questa tesi è quella di introdurre in Blender un Add-on in linguaggio Python che permetta di applicare alcune deformazioni di tipo surface-based a mesh poligonali. Questa tipologia di deformazioni rappresentano l’alternativa alle deformazioni di mesh poligonali tramite rigging ( cioè l’aggiunta di uno scheletro per controllare e per animare la mesh) e caging (cioè l’utilizzo di una struttura di controllo di tipo reticolare che propaga la sua deformazione su un oggetto in essa immerso), che di solito sono le prescelte in computer animation e in modellazione. Entrambe le deformazioni indicate sono già estremamente radicate in Blender, prova ne è il fatto che esiste più di un modificatore che le implementa, già integrato in codice nativo. Si introduce inizialmente la tecnica di deformazione di mesh poligonali tramite elasticità discreta, che è stata realizzata, quindi, presenteremo diverse metodologie di deformazione. Illustreremo poi come modellare, creare ed editare delle mesh in Blender. Non ci soffermeremo su dettagli puramente dettati dall’interfaccia utente, cercheremo invece di addentrarci nei concetti e nelle strutture teoriche, allo scopo di avere le basi logiche per definire una Add-on che risulti veramente efficace e utile all’interno del sistema di modellazione. Approfondiremo la struttura di due modificatori chiave per la deformazioni di mesh : Lattice Modifier e Mesh Deform Modifier che implementano una metodologia di tipo space-based. Infine ci concentreremo sulla parte di scripting Python in Blender. Daremo un’idea delle strutture dati, dei metodi e delle funzioni da utilizzare per interagire con l’ambiente circostante, con i singoli oggetti ed in particolare con le Mesh e daremo un esempio di script Python. Andremo infine a descrivere l’implementazione della deformazione elastica mediante add-on Python in Blender.

Una libreria OpenGL per la selezione e editing di mesh poligonali

Nel mondo Open Source, la libreria grafica OpenGL è oggi ampiamente utilizzata in svariati settori come l'animazione 2D/3D, la modellazione CAD o nello sviluppo di videogiochi. A causa dei suoi innumerevoli usi e dell'astrazione che OpenGL permette di ottenere su diversi ambienti grafici, lo sviluppatore - che la utilizza - è vincolato a cercare librerie di supporto al fine di sfruttarne al meglio le potenzialità. Questa tesi si configura su questi presupposti, presentando una libreria di selezione e editing di mesh 3D basata su OpenGL. La libreria, chiamata libEditMesh, sfrutta il meccanismo geometrico del RayPicking permettendo all'utilizzatore di identificare col mouse punti, facce e lati di solidi in scena. La tesi si articola sostanzialmente in due parti: nella prima vengono proposte alcune soluzioni ad-hoc sviluppate su applicazioni già esistenti nel panorama openSource, e non; nella seconda vengono esposti gli algoritmi e funzioni implementate in libEditMesh.

Modellazione di mesh tramite operatori booleani

Nella computer grafica, nell’ambito della modellazione geometrica, si fa uso delle operazioni booleane tra solidi per la manipolazione e la creazione di nuovi oggetti. Queste operazioni, quali unione, intersezione e differenza, vengono applicate alle superfici degli oggetti 3D esattamente come si fa su altri insiemi. In questo modo si riescono ad ottenere nuove forme complesse come combinazione delle altre, che sono in genere più semplici. Ciò che è stato realizzato in questo lavoro di tesi si colloca all’interno di un progetto preesistente, realizzato per consentire la manipolazione di modelli tridimensionali mediante l’utilizzo di operatori booleani: Mesh Glue. In questo lavoro, si è estesa la logica dell’applicazione degli operatori booleani, presente in Mesh Glue, per poter gestire anche scenari con mesh che presentano facce in tangenza. Inoltre, si è inserito Mesh Glue all’interno di un progetto più grande: Mesh Craft. Mesh Craft è un progetto che consiste in un ambiente di modellazione che utilizza come sistema di input il Leap Motion Controller, un dispositivo capace di identificare le dita di una mano e seguirne i movimenti con alta precisione.

Mesh shrinkage and pain in laparoscopic ventral hernia repair: a randomized clinical trial comparing suture versus tack mesh fixation

Mesh fixation during laparoscopic ventral hernia repair can be performed using transfascial sutures or metal tacks. The aim of the present study is to compare mesh shrinkage and pain between two different techniques of mesh fixation in a prospective randomized trial.

Sexual health of ethnic minority MSM in Britain (MESH project): design and methods

Background Men who have sex with men (MSM) remain the group most at risk of acquiring HIV infection in Britain. HIV prevalence appears to vary widely between MSM from different ethnic minority groups in this country for reasons that are not fully understood. The aim of the MESH project was to examine in detail the sexual health of ethnic minority MSM living in Britain. Methods/Design The main objectives of the MESH project were to explore among ethnic minority MSM living in Britain: (i) sexual risk behaviour and HIV prevalence; (ii) their experience of stigma and discrimination; (iii) disclosure of sexuality; (iv) use of, and satisfaction with sexual health services; (v) the extent to which sexual health services (for treatment and prevention) are aware of the needs of ethnic minority MSM. The research was conducted between 2006 and 2008 in four national samples: (i) ethnic minority MSM living in Britain; (ii) a comparison group of white British MSM living in Britain; (iii) NHS sexual health clinic staff in 15 British towns and cities with significant ethnic minority communities and; (iv) sexual health promotion/HIV prevention service providers. We also recruited men from two "key migrant" groups living in Britain: MSM born in Central or Eastern Europe and MSM born in Central or South America. Internet-based quantitative and qualitative research methods were used. Ethnic minority MSM were recruited through advertisements on websites, in community venues, via informal networks and in sexual health clinics. White and "key migrant" MSM were recruited mostly through Gaydar, one of the most popular dating sites used by gay men in Britain. MSM who agreed to take part completed a questionnaire online. Ethnic minority MSM who completed the online questionnaire were asked if they would be willing to take part in an online qualitative interview using email. Service providers were identified through the British Association of Sexual Health and HIV (BASHH) and the Terrence Higgins Trust (THT) CHAPS partnerships. Staff who agreed to take part were asked to complete a questionnaire online. The online survey was completed by 1241 ethnic minority MSM, 416 men born in South and Central America or Central and Eastern Europe, and 13,717 white British MSM; 67 ethnic minority MSM took part in the online qualitative interview. In addition 364 people working in sexual health clinics and 124 health promotion workers from around Britain completed an online questionnaire. Discussion The findings from this study will improve our understanding of the sexual health and needs of ethnic minority MSM in Britain.

Influence of Smoothing on Voxel-Based Mesh Accuracy in Micro-Finite Element

The interest in automatic volume meshing for finite element analysis (FEA) has grown more since the appearance of microfocus CT (μCT), due to its high resolution, which allows for the assessment of mechanical behaviour at a high precision. Nevertheless, the basic meshing approach of generating one hexahedron per voxel produces jagged edges. To prevent this effect, smoothing algorithms have been introduced to enhance the topology of the mesh. However, whether smoothing also improves the accuracy of voxel-based meshes in clinical applications is still under question. There is a trade-off between smoothing and quality of elements in the mesh. Distorted elements may be produced by excessive smoothing and reduce accuracy of the mesh. In the present work, influence of smoothing on the accuracy of voxel-based meshes in micro-FE was assessed. An accurate 3D model of a trabecular structure with known apparent mechanical properties was used as a reference model. Virtual CT scans of this reference model (with resolutions of 16, 32 and 64 μm) were then created and used to build voxel-based meshes of the microarchitecture. Effects of smoothing on the apparent mechanical properties of the voxel-based meshes as compared to the reference model were evaluated. Apparent Young’s moduli of the smooth voxel-based mesh were significantly closer to those of the reference model for the 16 and 32 μm resolutions. Improvements were not significant for the 64 μm, due to loss of trabecular connectivity in the model. This study shows that smoothing offers a real benefit to voxel-based meshes used in micro-FE. It might also broaden voxel-based meshing to other biomechanical domains where it was not used previously due to lack of accuracy. As an example, this work will be used in the framework of the European project ContraCancrum, which aims at providing a patient-specific simulation of tumour development in brain and lungs for oncologists. For this type of clinical application, such a fast, automatic, and accurate generation of the mesh is of great benefit.

Automated cement segmentation in vertebroplasty

Vertebroplasty is a minimally invasive procedure with many benefits; however, the procedure is not without risks and potential complications, of which leakage of the cement out of the vertebral body and into the surrounding tissues is one of the most serious. Cement can leak into the spinal canal, venous system, soft tissues, lungs and intradiscal space, causing serious neurological complications, tissue necrosis or pulmonary embolism. We present a method for automatic segmentation and tracking of bone cement during vertebroplasty procedures, as a first step towards developing a warning system to avoid cement leakage outside the vertebral body. We show that by using active contours based on level sets the shape of the injected cement can be accurately detected. The model has been improved for segmentation as proposed in our previous work by including a term that restricts the level set function to the vertebral body. The method has been applied to a set of real intra-operative X-ray images and the results show that the algorithm can successfully detect different shapes with blurred and not well-defined boundaries, where the classical active contours segmentation is not applicable. The method has been positively evaluated by physicians.

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.

Fully Automatic Segmentation of Brain Tumor Images using Support Vector Machine Classiffication in Combination with Hierarchical Conditional Random Field Regularization

Delineating brain tumor boundaries from magnetic resonance images is an essential task for the analysis of brain cancer. We propose a fully automatic method for brain tissue segmentation, which combines Support Vector Machine classification using multispectral intensities and textures with subsequent hierarchical regularization based on Conditional Random Fields. The CRF regularization introduces spatial constraints to the powerful SVM classification, which assumes voxels to be independent from their neighbors. The approach first separates healthy and tumor tissue before both regions are subclassified into cerebrospinal fluid, white matter, gray matter and necrotic, active, edema region respectively in a novel hierarchical way. The hierarchical approach adds robustness and speed by allowing to apply different levels of regularization at different stages. The method is fast and tailored to standard clinical acquisition protocols. It was assessed on 10 multispectral patient datasets with results outperforming previous methods in terms of segmentation detail and computation times.

Multi-Scale Modeling for Image Analysis of Brain Tumor Studies

Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multi-scale, multi-physics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlasbased segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.