Search results for "SEGMENTATION"
showing 10 items of 674 documents
Augmented reality based middle and inner ear surgical procedures
2020
Otologic procedures involve manipulation of small, delicate and complex structures in the temporal bone anatomy which are in close proxmity of critical nerves and blood vessels. Augmented reality (AR) can highly benefit the otological domain by providing supplementary anatomical and navigational information unified on a single display. However, despite being composed of mainly rigid bony structures, the awareness and acceptance of possibilities of AR systems in otology is fairly low. This project aims at developing video-based AR solutions for middle and inner ear surgical procedures.We propose two applications of AR in this regard. In the first application, information about middle ear cle…
Segmenting the spectators of national team sports: the case of a pre-competition match
2015
It has become common for academics and sports marketing professionals to study and explain the heterogeneity and complexity of sports spectators' behaviours and attitudes, with numerous works addressing this topic But these surveys are more about fans of professional sports clubs (soccer, basketball, baseball, hockey, etc) who attend regular season games in their favourite teams' home stadium or arena. To our knowledge, very few studies have been conducted into spectators of national teams. It is these spectators who are of the focus of this paper.
K-nearest neighbor driving active contours to delineate biological tumor volumes
2019
Abstract An algorithm for tumor delineation in positron emission tomography (PET) is presented. Segmentation is achieved by a local active contour algorithm, integrated and optimized with the k-nearest neighbor (KNN) classification method, which takes advantage of the stratified k-fold cross-validation strategy. The proposed approach is evaluated considering the delineation of cancers located in different body districts (i.e. brain, head and neck, and lung), and considering different PET radioactive tracers. Data are pre-processed in order to be expressed in terms of standardized uptake value, the most widely used PET quantification index. The algorithm uses an initial, operator selected re…
Hidden Markov Random Fields and Direct Search Methods for Medical Image Segmentation
2016
The goal of image segmentation is to simplify the representation of an image to items meaningful and easier to analyze. Medical image segmentation is one of the fundamental problems in image processing field. It aims to provide a crucial decision support to physicians. There is no one way to perform the segmentation. There are several methods based on HMRF. Hidden Markov Random Fields (HMRF) constitute an elegant way to model the problem of segmentation. This modelling leads to the minimization of an energy function. In this paper we investigate direct search methods that are Nelder-Mead and Torczon methods to solve this optimization problem. The quality of segmentation is evaluated on grou…
2016
AbstractMulticellular tumor spheroids (MCTSs) embedded in a matrix are re-emerging as a powerful alternative to monolayer-based cultures. The primary information gained from a three-dimensional model is the invasiveness of treatment-exposed MCTSs through the acquisition of light microscopy images. The amount and complexity of the acquired data and the bias arisen by their manual analysis are disadvantages calling for an automated, high-throughput analysis. We present a universal algorithm we developed with the scope of being robust enough to handle images of various qualities and various invasion profiles. The novelty and strength of our algorithm lie in: the introduction of a multi-step se…
Quantification and Characterization of Pulmonary Emphysema in Multislice-CT
2003
The new technology of the Multislice-CT provides volume data sets with approximately isotropic resolution, which permits a non invasive measurement of diffuse lung diseases like emphysema in the 3D space. The aim of our project is the development of a full automatic 3D CAD (Computer Aided Diagnosis) software tool for detection, quantification and characterization of emphysema in a thoracic CT data set. It should supply independently an analysis of an image data set to support the physician in clinical daily routine. In this paper we describe the developed 3D algorithms for the segmentation of the tracheo-bronchial tree, the lungs and the emphysema regions. We present different emphysema des…
Novel VAMPIRE algorithms for quantitative analysis of the retinal vasculature
2013
This paper summarizes three recent, novel algorithms developed within VAMPIRE, namely optic disc and macula detection, arteryvein classification, and enhancement of binary vessel masks, and their performance assessment. VAMPIRE is an international collaboration growing a suite of software tools to allow efficient quantification of morphological properties of the retinal vasculature in large collections of fundus camera images. VAMPIRE measurements are currently mostly used in biomarker research, i.e., investigating associations between the morphology of the retinal vasculature and a number of clinical and cognitive conditions.
Benchmarking Wilms’ tumor in multisequence MRI data: why does current clinical practice fail? Which popular segmentation algorithms perform well?
2019
Wilms' tumor is one of the most frequent malignant solid tumors in childhood. Accurate segmentation of tumor tissue is a key step during therapy and treatment planning. Since it is difficult to obtain a comprehensive set of tumor data of children, there is no benchmark so far allowing evaluation of the quality of human or computer-based segmentations. The contributions in our paper are threefold: (i) we present the first heterogeneous Wilms' tumor benchmark data set. It contains multisequence MRI data sets before and after chemotherapy, along with ground truth annotation, approximated based on the consensus of five human experts. (ii) We analyze human expert annotations and interrater varia…
Automatic estimation of Purkinje-Myocardial junction hot-spots from noisy endocardial samples: A simulation study
2017
The reconstruction of the ventricular cardiac conduction system (CCS) from patient-specific data is a challenging problem. High-resolution imaging techniques have allowed only the segmentation of proximal sections of the CCS from images acquired ex vivo. In this paper, we present an algorithm to estimate the location of a set of Purkinje-myocardial junctions (PMJs) from electro-anatomical maps, as those acquired during radio-frequency ablation procedures. The method requires a mesh representing the myocardium with local activation time measurements on a subset of nodes. We calculate the backwards propagation of the electrical signal from the measurement points to all the points in the mesh …