Image analysis for classification of dysplasia in Barrett’s esophagus using endoscopic optical coherence tomography

Barrett’s esophagus (BE) and associated adenocarcinoma have emerged as a major health care problem. Endoscopic optical coherence tomography is a microscopic sub-surface imaging technology that has been shown to differentiate tissue layers of the gastrointestinal wall and identify dysplasia in the mucosa, and is proposed as a surveillance tool to aid in management of BE. In this work a computer-aided diagnosis (CAD) system has been demonstrated for classification of dysplasia in Barrett’s esophagus using EOCT. The system is composed of four modules: region of interest segmentation, dysplasia-related image feature extraction, feature selection, and site classification and validation. Multiple feature extraction and classification methods were evaluated and the process of developing the CAD system is described in detail. Use of multiple EOCT images to classify a single site was also investigated. A total of 96 EOCT image-biopsy pairs (63 non-dysplastic, 26 low-grade and 7 high-grade dysplastic biopsy sites) from a previously described clinical study were analyzed using the CAD system, yielding an accuracy of 84% for classification of non-dysplastic vs. dysplastic BE tissue. The results motivate continued development of CAD to potentially enable EOCT surveillance of large surface areas of Barrett’s mucosa to identify dysplasia

Facilitating Colorectal Cancer Diagnosis with Computed Tomographic Colonography

Computed tomographic colonography (CTC) is a diagnostic technique involving helical volume acquisition of the cleansed, distended colorectum to detect colorectal cancer or potentially premalignant polyps. This Thesis summarises the evidence base, identifies areas in need of further research, quantifies sources of bias and presents novel techniques to facilitate colorectal cancer diagnosis using CTC. CTC literature is reviewed to justify the rationale for current implementation and to identify fruitful areas for research. This confirms excellent diagnostic performance can be attained providing CTC is interpreted by trained, experienced observers employing state-of-the-art implementation. The technique is superior to barium enema and consequently, it has been embraced by radiologists, clinicians and health policy-makers. Factors influencing generalisability of CTC research are investigated, firstly with a survey of European educational workshop participants which revealed limited CTC experience and training, followed by a systematic review exploring bias in research studies of diagnostic test accuracy which established that studies focussing on these aspects were lacking. Experiments to address these sources of bias are presented, using novel methodology: Conjoint analysis is used to ascertain patients‘ and clinicians’ attitudes to false-positive screening diagnoses, showing that both groups overwhelmingly value sensitivity over specificity. The results inform a weighted statistical analysis for CAD which is applied to the results of two previous studies showing the incremental benefit is significantly higher for novices than experienced readers. We have employed eye-tracking technology to establish the visual search patterns of observers reading CTC, demonstrated feasibility and developed metrics for analysis. We also describe development and validation of computer software to register prone and supine endoluminal surface locations demonstrating accurate matching of corresponding points when applied to a phantom and a generalisable, publically available, CTC database. Finally, areas in need of future development are suggested

Estudo de algoritmos para detectar pólipos em vídeo de endo-cápsula

Mestrado em Engenharia Electrónica e TelecomunicaçõesA cápsula endoscópica está disponível para diagnóstico desde 2001, altura em que recebeu a aprovação da Food Drug and Administration (FDA) e a certificação CE. A sua utilização está a crescer criando um novo mercado para ferramentas tecnológicas de detecção automática de eventos, de forma a diminuir a necessidade de visualização do exame completo por parte dos médicos. O primeiro objectivo a extrair deste trabalho foi o desenvolvimento de uma ferramenta de software de catalogação de imagem de cápsula endoscópica para obter um conjunto de dados bem anotado para ajudar no desenvolvimento de algoritmos computacionais de ajuda ao diagnóstico automático. Um segundo objectivo deste trabalho foi a validação de duas metodologias de análise de textura aplicadas com o intuito de detectar eventos em vídeo endoscópico. Os resultados obtidos demonstram a dificuldade de utilização de tais meios para a detecção dos referidos eventos em vídeo de cápsula endoscópica. ABSTRACT: The endoscopic capsule is available for medical use since 2001, when FDA and CE gave their approval as means to diagnose gastrointestinal diseases. Its exponential use is creating a new market for computational tools that can detect events automatically. Therefore aiding doctors on diagnosing exams. The main goal of this work was the creation of a software tool for catalog images from endoscopic capsule video, obtaining a well annotated dataset for aiding the development of computer aided diagnosis algorithms. The next objective was the validation of two methodologies of image texture analysis applied and implemented to detect abnormal events on endoscopic video. The results had shown the difficulty of such means to detect those events using endoscopic capsule video

Blood Vessel Segmentation and shape analysis for quantification of Coronary Artery Stenosis in CT Angiography

This thesis presents an automated framework for quantitative vascular shape analysis of the coronary arteries, which constitutes an important and fundamental component of an automated image-based diagnostic system. Firstly, an automated vessel segmentation algorithm is developed to extract the coronary arteries based on the framework of active contours. Both global and local intensity statistics are utilised in the energy functional calculation, which allows for dealing with non-uniform brightness conditions, while evolving the contour towards to the desired boundaries without being trapped in local minima. To suppress kissing vessel artifacts, a slice-by-slice correction scheme, based on multiple regions competition, is proposed to identify and track the kissing vessels throughout the transaxial images of the CTA data. Based on the resulting segmentation, we then present a dedicated algorithm to estimate the geometric parameters of the extracted arteries, with focus on vessel bifurcations. In particular, the centreline and associated reference surface of the coronary arteries, in the vicinity of arterial bifurcations, are determined by registering an elliptical cross sectional tube to the desired constituent branch. The registration problem is solved by a hybrid optimisation method, combining local greedy search and dynamic programming, which ensures the global optimality of the solution and permits the incorporation of any hard constraints posed to the tube model within a natural and direct framework. In contrast with conventional volume domain methods, this technique works directly on the mesh domain, thus alleviating the need for image upsampling. The performance of the proposed framework, in terms of efficiency and accuracy, is demonstrated on both synthetic and clinical image data. Experimental results have shown that our techniques are capable of extracting the major branches of the coronary arteries and estimating the related geometric parameters (i.e., the centreline and the reference surface) with a high degree of agreement to those obtained through manual delineation. Particularly, all of the major branches of coronary arteries are successfully detected by the proposed technique, with a voxel-wise error at 0.73 voxels to the manually delineated ground truth data. Through the application of the slice-by-slice correction scheme, the false positive metric, for those coronary segments affected by kissing vessel artifacts, reduces from 294% to 22.5%. In terms of the capability of the presented framework in defining the location of centrelines across vessel bifurcations, the mean square errors (MSE) of the resulting centreline, with respect to the ground truth data, is reduced by an average of 62.3%, when compared with initial estimation obtained using a topological thinning based algorithm

Blood vessel segmentation and shape analysis for quantification of coronary artery stenosis in CT angiography

This thesis presents an automated framework for quantitative vascular shape analysis of the coronary arteries, which constitutes an important and fundamental component of an automated image-based diagnostic system. Firstly, an automated vessel segmentation algorithm is developed to extract the coronary arteries based on the framework of active contours. Both global and local intensity statistics are utilised in the energy functional calculation, which allows for dealing with non-uniform brightness conditions, while evolving the contour towards to the desired boundaries without being trapped in local minima. To suppress kissing vessel artifacts, a slice-by-slice correction scheme, based on multiple regions competition, is proposed to identify and track the kissing vessels throughout the transaxial images of the CTA data. Based on the resulting segmentation, we then present a dedicated algorithm to estimate the geometric parameters of the extracted arteries, with focus on vessel bifurcations. In particular, the centreline and associated reference surface of the coronary arteries, in the vicinity of arterial bifurcations, are determined by registering an elliptical cross sectional tube to the desired constituent branch. The registration problem is solved by a hybrid optimisation method, combining local greedy search and dynamic programming, which ensures the global optimality of the solution and permits the incorporation of any hard constraints posed to the tube model within a natural and direct framework. In contrast with conventional volume domain methods, this technique works directly on the mesh domain, thus alleviating the need for image upsampling. The performance of the proposed framework, in terms of efficiency and accuracy, is demonstrated on both synthetic and clinical image data. Experimental results have shown that our techniques are capable of extracting the major branches of the coronary arteries and estimating the related geometric parameters (i.e., the centreline and the reference surface) with a high degree of agreement to those obtained through manual delineation. Particularly, all of the major branches of coronary arteries are successfully detected by the proposed technique, with a voxel-wise error at 0.73 voxels to the manually delineated ground truth data. Through the application of the slice-by-slice correction scheme, the false positive metric, for those coronary segments affected by kissing vessel artifacts, reduces from 294% to 22.5%. In terms of the capability of the presented framework in defining the location of centrelines across vessel bifurcations, the mean square errors (MSE) of the resulting centreline, with respect to the ground truth data, is reduced by an average of 62.3%, when compared with initial estimation obtained using a topological thinning based algorithm.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

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