Improved 3D thinning algorithms for skeleton extraction

In this study, we focused on developing a novel 3D Thinning algorithm to extract one-voxel wide skeleton from various 3D objects aiming at preserving the topological information. The 3D Thinning algorithm was testified on computer-generated and real 3D reconstructed image sets acquired from TEMT and compared with other existing 3D Thinning algorithms. It is found that the algorithm has conserved medial axes and simultaneously topologies very well, demonstrating many advantages over the existing technologies. They are versatile, rigorous, efficient and rotation invariant.<br /

Dissection of C. elegans behavioral genetics in 3-D environments

The nematode Caenorhabditis elegans is a widely used model for genetic dissection of animal behaviors. Despite extensive technical advances in imaging methods, it remains challenging to visualize and quantify C. elegans behaviors in three-dimensional (3-D) natural environments. Here we developed an innovative 3-D imaging method that enables quantification of C. elegans behavior in 3-D environments. Furthermore, for the first time, we characterized 3-D-specific behavioral phenotypes of mutant worms that have defects in head movement or mechanosensation. This approach allowed us to reveal previously unknown functions of genes in behavioral regulation. We expect that our 3-D imaging method will facilitate new investigations into genetic basis of animal behaviors in natural 3-D environments

A new method for pore structure quantification and pore network extraction from SEM images

C.W. thanks China Scholarship Council’s financial support for his Ph.D. study. The authors thank Anasuria Operating Company Limited (AOC) for making available the core plug samples. We thank the two reviewers for their insight comments and constructive suggestions toward improving our manuscript. Finally, we thank John Still (University of Aberdeen Centre for Electron Microscopy, Analysis and Characterisation (ACEMAC)) for invaluable assistance in the acquisition of SEM images.Peer reviewedPostprin

Intensity-Based Skeletonization of CryoEM Gray-Scale Images Using a True Segmentation-Free Algorithm

Cryo-electron microscopy is an experimental technique that is able to produce 3D gray-scale images of protein molecules. In contrast to other experimental techniques, cryo-electron microscopy is capable of visualizing large molecular complexes such as viruses and ribosomes. At medium resolution, the positions of the atoms are not visible and the process cannot proceed. The medium-resolution images produced by cryo-electron microscopy are used to derive the atomic structure of the proteins in de novo modeling. The skeletons of the 3D gray-scale images are used to interpret important information that is helpful in de novo modeling. Unfortunately, not all features of the image can be captured using a single segmentation. In this paper, we present a segmentation-free approach to extract the gray-scale curve-like skeletons. The approach relies on a novel representation of the 3D image, where the image is modeled as a graph and a set of volume trees. A test containing 36 synthesized maps and one authentic map shows that our approach can improve the performance of the two tested tools used in de novo modeling. The improvements were 62 and 13 percent for Gorgon and DP-TOSS, respectively

Towards development of automatic path planning system in image-guided neurosurgery

With the advent of advanced computer technology, many computer-aided systems have evolved to assist in medical related work including treatment, diagnosis, and even surgery. In modern neurosurgery, Magnetic Resonance Image guided stereotactic surgery exactly complies with this trend. It is a minimally invasive operation being much safer than the traditional open-skull surgery, and offers higher precision and more effective operating procedures compared to conventional craniotomy. However, such operations still face significant challenges of planning the optimal neurosurgical path in order to reach the ideal position without damage to important internal structures. This research aims to address this major challenge. The work begins with an investigation of the problem of distortion induced by MR images. It then goes on to build a template of the Circle of Wills brain vessels, realized from a collection of Magnetic Resonance Angiography images, which is needed to maintain operating standards when, as in many cases, Magnetic Resonance Angiography images are not available for patients. Demographic data of brain tumours are also studied to obtain further understanding of diseased human brains through the development of an effect classifier. The developed system allows the internal brain structure to be ‘seen’ clearly before the surgery, giving surgeons a clear picture and thereby makes a significant contribution to the eventual development of a fully automatic path planning system

Segmentation of 3D image data using advanced textural and shape features

Tato diplomová práce se zabývá nejprve teoretickým popisem řady metod texturní a tvarové analýzy. Tyto metody jsou v několika publikovaných článcích využity pro automatickou detekci lézí v páteři na CT snímcích, v této práci jsou některé z těchto článků krátce prezentovány. Dále diplomová práce obsahuje popis různých klasifikátorů, které se využívají pro klasifikaci příznakových vektorů odvozených uvedenými metodami. Realizační částí práce je návrh a implementace vlastního řešení segmentace obrazových dat (metastatických lézí v obratlích) s využitím klasifikace příznakových vektorů tvořených texturními a tvarovými příznaky. Práce se také věnuje výběru významných příznaků pro segmentaci. Segmentační algoritmus je testován na medicínských datech.This thesis first describes theory of range of methods of textural and shape analysis. In several published articles some of the mentioned methods are used for automatic detection of lesion in spine in CT images. Some of these articles are shortly presented (in this thesis). Next part of the thesis includes description of various classifiers which are used for classification of feature vectors. Practical part of the thesis is a design and implementation of image data segmentation solution (metastatic lesions in vertebrae) with use of classification of feature vectors formed by texture and shape symptoms. The thesis also deals with the selection of significant features for segmentation. Segmentation algorithm is tested on medical data.

Desarrollo de algoritmo rápido de esqueletonización de estructuras óseas en 3D a partir de imágenes médicas

La esqueletonización pretende obtener de un objeto, un patrón continúo que lo represente con la menor cantidad de datos posibles. Con el fin de llevar a cabo dicho proceso existen diferentes métodos. Todos ellos tienen por objetivo la eliminación de puntos del objeto hasta obtener la curva o superficie media de menor espesor que define su forma. Sin embargo, el proceso utilizado para conseguirlo es diferente y por lo tanto, los principales métodos para la esqueletonización se pueden clasificar en tres clases: basados en Adelgazamiento, basados en Transformada de la Distancia y basados en Diagramas de Voronoi. En el presente proyecto se comparan estas tres clases y se analizan sus ventajas y desventajas. Para ello, se estudian los resultados obtenidos al aplicar una serie de algoritmos pertenecientes a cada clase con la finalidad de identificar la metodología más adecuada y desarrollar su versión 3D. Así pues, se presenta un nuevo algoritmo de esqueletonización 3D basado en la transformada de la distancia que extrae el esqueleto de estructuras óseas a partir de imágenes médicas adquiridas mediante resonancia magnética. La intención es conseguir modelos más simples de la estructura del tejido trabecular que nos permitan evaluar la respuesta mecánica y la influencia de la erosión en el hueso mediante simulaciones de estas estructuras.Mompeán Escartí, MI. (2012). Desarrollo de algoritmo rápido de esqueletonización de estructuras óseas en 3D a partir de imágenes médicas. http://hdl.handle.net/10251/17008.Archivo delegad

Estudo e desenvolvimento de algoritmos de esqueletização com aplicação em redes vasculares ósseas

Although a common technique, the radiotherapy can cause damage to bone repair, such as decrease in vascularization. However, the bone vascular network has an important role in capacity of bone regeneration because it provides oxygen and nutrients, therefore, tools that helps the analysis of vascular networks are important for the study of various therapies that have influence on the bone repair. In order to analyze such networks, we mande three-dimensional reconstructions of collected images from the sectioning of a mouse femurs that received radiation doses in the left femur, while the right was not irradiated and used for control. In order to aid the analysis of these volumes, skeletonization techniques were used to decrease the amount of the objects’s information and make the analysis more accurate and efficient. However, there are several types of skeletonization algorithms which uses different approachs as based on Forcefield, Thinning, based on Distance Transform, Geometrical and based on Wave Propagation. In order to analyze which of them produces the best results in vascular networks, an implementation of each type was chosen to be tested and analyzed in vascular network volumes. Furthermore, the algorithm chosen to represent the methods based on Wave Propagation was developed and proposed in this work exclusively to extract vascular networks. Finally, the skeletons of the vascular networks reproduced the network studied with clarity and enabled the conclusion of analysis related to the radiation impact on vascular topology. In addition, the comparison between the types of skeletonization algorithms allowed a deep study about the subject and on the various curve skeletons characteristics that can be used to classify and compare the methods in the literature.Dissertação (Mestrado)Apesar de ser uma técnica muito difundida, a radioterapia pode causar danos ao reparo ósseo, como por exemplo, a diminuição da vascularização. Entretanto, a rede vascular óssea tem um papel importante na capacidade de regeneração dos ossos, pois fornece oxigênio e nutrientes essenciais, logo, ferramentas que auxiliem a análise dessas redes são importantes para o estudo de diversas terapias que têm influência sobre o tecido ósseo. Para analisar tais redes foi feita a reconstrução tridimensional de imagens coletadas a partir do seccionamento dos fêmures de um rato que recebeu doses de radiação em seu fêmur esquerdo, enquanto que o direito não foi irradiado sendo, portanto, utilizado para controle. Com o objetivo de auxiliar a análise desses volumes foi utilizada a técnica de esqueletização, que tem a finalidade de diminuir a quantidade de informação dos objetos e tornar a análise mais precisa e eficiente. Entretanto, existem diversos tipos de algoritmos esqueletização, sendo eles, de Afinamento, Geométricos, baseados na Transformada Distância, em Campo de Força e em Propagação de Ondas. Com o objetivo de analisar qual deles produz melhores resultados em volumes de redes vasculares foi escolhida uma implementação de cada tipo para ser testada e analisada em volumes pertencentes às redes vasculares. Além disso, o algoritmo escolhido para representar os métodos baseados em Propagação de Ondas foi desenvolvido e proposto neste trabalho exclusivamente para extrair canais de redes vasculares. Por fim, os esqueletos das redes vasculares conseguiram reproduzir com clareza a rede estudada e possibilitaram a conclusão de análises relacionadas ao impacto da radioterapia sobre a topologia vascular. Além disso, a comparação entre os tipos de algoritmos de esqueletização possibilitou um estudo aprofundado sobre o tema e sobre as diversas características de esqueletos de curva que podem ser usadas para classificar e comparar os métodos presentes na literatura