Accurate geometry reconstruction of vascular structures using implicit splines

3-D visualization of blood vessel from standard medical datasets (e.g. CT or MRI) play an important role in many clinical situations, including the diagnosis of vessel stenosis, virtual angioscopy, vascular surgery planning and computer aided vascular surgery. However, unlike other human organs, the vasculature system is a very complex network of vessel, which makes it a very challenging task to perform its 3-D visualization. Conventional techniques of medical volume data visualization are in general not well-suited for the above-mentioned tasks. This problem can be solved by reconstructing vascular geometry. Although various methods have been proposed for reconstructing vascular structures, most of these approaches are model-based, and are usually too ideal to correctly represent the actual variation presented by the cross-sections of a vascular structure. In addition, the underlying shape is usually expressed as polygonal meshes or in parametric forms, which is very inconvenient for implementing ramification of branching. As a result, the reconstructed geometries are not suitable for computer aided diagnosis and computer guided minimally invasive vascular surgery. In this research, we develop a set of techniques associated with the geometry reconstruction of vasculatures, including segmentation, modelling, reconstruction, exploration and rendering of vascular structures. The reconstructed geometry can not only help to greatly enhance the visual quality of 3-D vascular structures, but also provide an actual geometric representation of vasculatures, which can provide various benefits. The key findings of this research are as follows: 1. A localized hybrid level-set method of segmentation has been developed to extract the vascular structures from 3-D medical datasets. 2. A skeleton-based implicit modelling technique has been proposed and applied to the reconstruction of vasculatures, which can achieve an accurate geometric reconstruction of the vascular structures as implicit surfaces in an analytical form. 3. An accelerating technique using modern GPU (Graphics Processing Unit) is devised and applied to rendering the implicitly represented vasculatures. 4. The implicitly modelled vasculature is investigated for the application of virtual angioscopy

Techniques, Clinical Applications and Limitations of 3D Reconstruction in CT of the Abdomen

Enhanced z-axis coverage with thin overlapping slices in breath-hold acquisitions with multidetector CT (MDCT) has considerably enhanced the quality of multiplanar 3D reconstruction. This pictorial essay describes the improvements in 3D reconstruction and technical aspects of 3D reconstruction and rendering techniques available for abdominal imaging. Clinical applications of 3D imaging in abdomen including liver, pancreaticobiliary system, urinary and gastrointestinal tracts and imaging before and after transplantation are discussed. In addition, this article briefly discusses the disadvantages of thin-slice acquisitions including increasing numbers of transverse images, which must be reviewed by the radiologist

Large Model Visualization : Techniques and Applications

The size of datasets in scientific computing is rapidly increasing. This increase is caused by a boost of processing power in the past years, which in turn was invested in an increase of the accuracy and the size of the models. A similar trend enabled a significant improvement of medical scanners; more than 1000 slices of a resolution of 512x512 can be generated by modern scanners in daily practice. Even in computer-aided engineering typical models eas-ily contain several million polygons. Unfortunately, the data complexity is growing faster than the rendering performance of modern computer systems. This is not only due to the slower growing graphics performance of the graphics subsystems, but in particular because of the significantly slower growing memory bandwidth for the transfer of the geometry and image data from the main memory to the graphics accelerator. Large model visualization addresses this growing divide between data complexity and rendering performance. Most methods focus on the reduction of the geometric or pixel complexity, and hence also the memory bandwidth requirements are reduced. In this dissertation, we discuss new approaches from three different research areas. All approaches target at the reduction of the processing complexity to achieve an interactive visualization of large datasets. In the second part, we introduce applications of the presented ap-proaches. Specifically, we introduce the new VIVENDI system for the interactive virtual endoscopy and other applications from mechanical engineering, scientific computing, and architecture.The size of datasets in scientific computing is rapidly increasing. This increase is caused by a boost of processing power in the past years, which in turn was invested in an increase of the accuracy and the size of the models. A similar trend enabled a significant improvement of medical scanners; more than 1000 slices of a resolution of 512x512 can be generated by modern scanners in daily practice. Even in computer-aided engineering typical models eas-ily contain several million polygons. Unfortunately, the data complexity is growing faster than the rendering performance of modern computer systems. This is not only due to the slower growing graphics performance of the graphics subsystems, but in particular because of the significantly slower growing memory bandwidth for the transfer of the geometry and image data from the main memory to the graphics accelerator. Large model visualization addresses this growing divide between data complexity and rendering performance. Most methods focus on the reduction of the geometric or pixel complexity, and hence also the memory bandwidth requirements are reduced. In this dissertation, we discuss new approaches from three different research areas. All approaches target at the reduction of the processing complexity to achieve an interactive visualization of large datasets. In the second part, we introduce applications of the presented ap-proaches. Specifically, we introduce the new VIVENDI system for the interactive virtual endoscopy and other applications from mechanical engineering, scientific computing, and architecture

SURGICAL NAVIGATION AND AUGMENTED REALITY FOR MARGINS CONTROL IN HEAD AND NECK CANCER

I tumori maligni del distretto testa-collo rappresentano un insieme di lesioni dalle diverse caratteristiche patologiche, epidemiologiche e prognostiche. Per una porzione considerevole di tali patologie, l’intervento chirurgico finalizzato all’asportazione completa del tumore rappresenta l’elemento chiave del trattamento, quand’anche esso includa altre modalità quali la radioterapia e la terapia sistemica. La qualità dell’atto chirurgico ablativo è pertanto essenziale al fine di garantire le massime chance di cura al paziente. Nell’ambito della chirurgia oncologica, la qualità delle ablazioni viene misurata attraverso l’analisi dello stato dei margini di resezione. Oltre a rappresentare un surrogato della qualità della resezione chirurgica, lo stato dei margini di resezione ha notevoli implicazioni da un punto di vista clinico e prognostico. Infatti, il coinvolgimento dei margini di resezione da parte della neoplasia rappresenta invariabilmente un fattore prognostico sfavorevole, oltre che implicare la necessità di intensificare i trattamenti postchirurgici (e.g., ponendo indicazione alla chemioradioterapia adiuvante), comportando una maggiore tossicità per il paziente. La proporzione di resezioni con margini positivi (i.e., coinvolti dalla neoplasia) nel distretto testa-collo è tra le più elevate in ambito di chirurgia oncologica. In tale contesto si pone l’obiettivo del dottorato di cui questa tesi riporta i risultati. Le due tecnologie di cui si è analizzata l’utilità in termini di ottimizzazione dello stato dei margini di resezione sono la navigazione chirurgica con rendering tridimensionale e la realtà aumentata basata sulla videoproiezione di immagini. Le sperimentazioni sono state svolte parzialmente presso l’Università degli Studi di Brescia, parzialmente presso l’Azienda Ospedale Università di Padova e parzialmente presso l’University Health Network (Toronto, Ontario, Canada). I risultati delle sperimentazioni incluse in questo elaborato dimostrano che l'impiego della navigazione chirurgica con rendering tridimensionale nel contesto di procedure oncologiche ablative cervico-cefaliche risulta associata ad un vantaggio significativo in termini di riduzione della frequenza di margini positivi. Al contrario, le tecniche di realtà aumentata basata sulla videoproiezione, nell'ambito della sperimentazione preclinica effettuata, non sono risultate associate a vantaggi sufficienti per poter considerare tale tecnologia per la traslazione clinica.Head and neck malignancies are an heterogeneous group of tumors. Surgery represents the mainstay of treatment for the large majority of head and neck cancers, with ablation being aimed at removing completely the tumor. Radiotherapy and systemic therapy have also a substantial role in the multidisciplinary management of head and neck cancers. The quality of surgical ablation is intimately related to margin status evaluated at a microscopic level. Indeed, margin involvement has a remarkably negative effect on prognosis of patients and mandates the escalation of postoperative treatment by adding concomitant chemotherapy to radiotherapy and accordingly increasing the toxicity of overall treatment. The rate of margin involvement in the head and neck is among the highest in the entire field of surgical oncology. In this context, the present PhD project was aimed at testing the utility of 2 technologies, namely surgical navigation with 3-dimensional rendering and pico projector-based augmented reality, in decreasing the rate of involved margins during oncologic surgical ablations in the craniofacial area. Experiments were performed in the University of Brescia, University of Padua, and University Health Network (Toronto, Ontario, Canada). The research activities completed in the context of this PhD course demonstrated that surgical navigation with 3-dimensional rendering confers a higher quality to oncologic ablations in the head and neck, irrespective of the open or endoscopic surgical technique. The benefits deriving from this implementation come with no relevant drawbacks from a logistical and practical standpoint, nor were major adverse events observed. Thus, implementation of this technology into the standard care is the logical proposed step forward. However, the genuine presence of a prognostic advantage needs longer and larger study to be formally addressed. On the other hand, pico projector-based augmented reality showed no sufficient advantages to encourage translation into the clinical setting. Although observing a clear practical advantage deriving from the projection of osteotomy lines onto the surgical field, no substantial benefits were measured when comparing this technology with surgical navigation with 3-dimensional rendering. Yet recognizing a potential value of this technology from an educational standpoint, the performance displayed in the preclinical setting in terms of surgical margins optimization is not in favor of a clinical translation with this specific aim

Intraoperative Endoscopic Augmented Reality in Third Ventriculostomy

In neurosurgery, as a result of the brain-shift, the preoperative patient models used as a intraoperative reference change. A meaningful use of the preoperative virtual models during the operation requires for a model update. The NEAR project, Neuroendoscopy towards Augmented Reality, describes a new camera calibration model for high distorted lenses and introduces the concept of active endoscopes endowed with with navigation, camera calibration, augmented reality and triangulation modules