Computerized Analysis of Magnetic Resonance Images to Study Cerebral Anatomy in Developing Neonates

The study of cerebral anatomy in developing neonates is of great importance for the understanding of brain development during the early period of life. This dissertation therefore focuses on three challenges in the modelling of cerebral anatomy in neonates during brain development. The methods that have been developed all use Magnetic Resonance Images (MRI) as source data. To facilitate study of vascular development in the neonatal period, a set of image analysis algorithms are developed to automatically extract and model cerebral vessel trees. The whole process consists of cerebral vessel tracking from automatically placed seed points, vessel tree generation, and vasculature registration and matching. These algorithms have been tested on clinical Time-of- Flight (TOF) MR angiographic datasets. To facilitate study of the neonatal cortex a complete cerebral cortex segmentation and reconstruction pipeline has been developed. Segmentation of the neonatal cortex is not effectively done by existing algorithms designed for the adult brain because the contrast between grey and white matter is reversed. This causes pixels containing tissue mixtures to be incorrectly labelled by conventional methods. The neonatal cortical segmentation method that has been developed is based on a novel expectation-maximization (EM) method with explicit correction for mislabelled partial volume voxels. Based on the resulting cortical segmentation, an implicit surface evolution technique is adopted for the reconstruction of the cortex in neonates. The performance of the method is investigated by performing a detailed landmark study. To facilitate study of cortical development, a cortical surface registration algorithm for aligning the cortical surface is developed. The method first inflates extracted cortical surfaces and then performs a non-rigid surface registration using free-form deformations (FFDs) to remove residual alignment. Validation experiments using data labelled by an expert observer demonstrate that the method can capture local changes and follow the growth of specific sulcus

From point cloud to textured model the Zamani laser scanning pipeline in heritage documentation

The paper describes the stages of the laser scanning pipeline from data acquisition to the final 3D computer model based on experiences gained during the ongoing creation of data for the African Cultural Heritage Sites and Landscapes database. The various processes are briefly discussed and challenges are highlighted which need to be addressed to develop the full potential of laser scanning. Experiences with fieldwork, scan registration, hole-filling, data cleaning, modelling and texturing are reported. The potential strengths and weaknesses of the emerging tool of “Structure from Motion” are briefly explored for their potential use in combination with laser scanning

From Point Cloud to Textured Model, the Zamani Laser Scanning Pipeline in Heritage Documentation

The paper describes the stages of the laser scanning pipeline from data acquisition to the final 3D computer model based on experiences gained during the ongoing creation of data for the African Cultural Heritage Sites and Landscapes database. The various processes are briefly discussed and challenges are highlighted which need to be addressed to develop the full potential of laser scanning. Experiences with fieldwork, scan registration, hole-filling, data cleaning, modelling and texturing are reported. The potential strengths and weaknesses of the emerging tool of “Structure from Motion” are briefly explored for their potential use in combination with laser scanning

Creating 3D models of cultural heritage sites with terrestrial laser scanning and 3D imaging

Includes abstract.Includes bibliographical references.The advent of terrestrial laser-scanners made the digital preservation of cultural heritage sites an affordable technique to produce accurate and detailed 3D-computermodel representations for any kind of 3D-objects, such as buildings, infrastructure, and even entire landscapes. However, one of the key issues with this technique is the large amount of recorded points; a problem which was even more intensified by the recent advances in laser-scanning technology, which increased the data acquisition rate from 25 thousand to 1 million points per second. The following research presents a workflow for the processing of large-volume laser-scanning data, with a special focus on the needs of the Zamani initiative. The research project, based at the University of Cape Town, spatially documents African Cultural Heritage sites and Landscapes and produces meshed 3D models, of various, historically important objects, such as fortresses, mosques, churches, castles, palaces, rock art shelters, statues, stelae and even landscapes

Methods for Procedural Terrain Generation

Procedural generation has been utilized in the automatic generation of data for a long time. This automated processing has been utilized in the entertainment industry as well as in research work in order to be able to quickly produce large amounts of just the kind of data needed, for example, in system testing. In this thesis, we examine different ways to utilize procedural generation to produce different synthetic terrains. First, we will take a closer look at what procedural generation is, where it originally started, and where it was utilized. From this we move on to look at how this technology is utilized in the creation of terrains and what terrain is generally visually required. From this we move on to look at different ways to implement terrain generation. As part of this thesis, we have selected three methods and implemented our own implementations for terrain generation. We look at the performance of these implementations, and what a test group thinks about those synthetic terrains. The results obtained from this are analyzed and presented at the end of the thesis.Proseduraalista generointia on hyödynnetty datan automaattisessa tuottamisessa jo pitkään. Tätä automatisoitua prosessointia on niin hyödynnetty viihdeteollisuudessa kuin tutkimustyössä, jotta ollaan voitu tuottaa nopeasti suuria määriä juuri sellaista dataa kuin tarvitaan esimerkiksi järjestelmän testauksessa. Tässä tutkielmassa tarkastellaan erilaisia tapoja hyödyntää proseduraalista generointia erilaisten synteettisten maastojen tuottamiseksi. Aluksi tutustutaan hieman tarkemmin siihen mitä proseduraalinen generointi on, mistä se on alunperin lähtenyt ja mihin sitä on hyödynnetty. Tästä siirrytään tarkastelemaan miten kyseistä tekniikkaa hyödynnetään maastojen luomisessa ja mitä maastoilta yleensä visuaalisesti vaaditaan. Tästä siirrytään tarkastelemaan eri tapoja toteuttaa maaston generointia. Osana tätä tutkielmaa, on valittu kolme menetelmää ja laadittu niistä kullekin oma toteutus maaston generointiin. Työssä tarkastellaan näiden toteutusten suoritustuloksia, ja mitä mieltä testiryhmä on kyseisistä synteettisistä maastoista. Saadut tulokset ja niiden analyyysi esitellään tutkielman lopussa