Search results for "Segmentation"

Modular Method of Detection, Localization and Counting of Mutliple-Taxon Pollen Apertures Using Bag of Words

2014

International audience; Accurate recognition of airborne pollen taxa is crucial for understanding and treating allergic diseases, which affect an important proportion of the world population. Modern computer vision techniques enables the detection of discriminant characteristics. Apertures is one of these characteristic that has been little explored up to now. In this paper, a flexible method of detection, localization and counting of apertures of different pollen taxa with varying appearances is proposed. Apertures are described based by primitive images following the Bag-of-Words strat-egy. A confidence map is estimated based on the classification of sampled regions. The method is designe…

Real-time image segmentation for anomalies detection using SVM approximation

2003

In this paper, we propose a method of implementation improvement of the decision rule of the support vector machine, applied to real-time image segmentation. We present very high speed decisions (approximately 10 ns per pixel) which can be useful for detection of anomalies on manufactured parts. We propose an original combination of classifiers allowing fast and robust classification applied to image segmentation. The SVM is used during a first step, pre-processing the training set and thus rejecting any ambiguities. The hyperrectangles-based learning algorithm is applied using the SVM classified training set. We show that the hyperrectangle method imitates the SVM method in terms of perfor…

A completely automated CAD system for mass detection in a large mammographic database

2006

Mass localization plays a crucial role in computer-aided detection (CAD) systems for the classification of suspicious regions in mammograms. In this article we present a completely automated classification system for the detection of masses in digitized mammographic images. The tool system we discuss consists in three processing levels: (a) Image segmentation for the localization of regions of interest (ROIs). This step relies on an iterative dynamical threshold algorithm able to select iso-intensity closed contours around gray level maxima of the mammogram. (b) ROI characterization by means of textural features computed from the gray tone spatial dependence matrix (GTSDM), containing secon…

Large scale semi-supervised image segmentation with active queries

2011

A semiautomatic procedure to generate classification maps of remote sensing images is proposed. Starting from a hierarchical unsupervised classification, the algorithm exploits the few available labeled pixels to assign each cluster to the most probable class. For a given amount of labeled pixels, the algorithm returns a classified segmentation map, along with confidence levels of class membership for each pixel. Active learning methods are used to select the most informative samples to increase confidence in the class membership. Experiments on a AVIRIS hyperspectral image confirm the effectiveness of the method, especially when used with active learning query functions and spatial regular…

2020

One crucial parameter to evaluate the state of the heart after myocardial infarction (MI) is the viability of the myocardial segment, i.e., if the segment recovers its functionality upon revascularization. MRI performed several minutes after the injection of a contrast agent (delayed enhancement-MRI or DE-MRI) is a method of choice to evaluate the extent of MI, and by extension, to assess viable tissues after an injury. The Emidec dataset is composed of a series of exams with DE-MR images in short axis orientation covering the left ventricle from normal cases or patients with myocardial infarction, with the contouring of the myocardium and diseased areas (if present) from experts in the dom…

Graph cut-based method for segmenting the left ventricle from MRI or echocardiographic images

2017

International audience; In this paper, we present a fast and interactive graph cut method for 3D segmentation of the endocardial wall of the left ventricle (LV) adapted to work on two of the most widely used modalities: magnetic resonance imaging (MRI) and echocardiography. Our method accounts for the fundamentally different nature of both modalities: 3D echocardiographic images have a low contrast, a poor signal-to-noise ratio and frequent signal drop, while MR images are more detailed but also cluttered and contain highly anisotropic voxels. The main characteristic of our method is to work in a 3D Bezier coordinate system instead of the original Euclidean space. This comes with several ad…

Image Segmentation and Object Extraction for Automatic Diatoms Classification

2018

The diatoms are unicellular algae of great interest in paleontology, aquatic ecology, and forensic medicine, among others. Currently, there are more than 100 000 known species distributed in aquatic ecosystems. For that reason, there is a big interest in the automatic classification of diatom images, however, the preliminary process applied to isolate the diatom from the background is a complex task. In this paper, we propose a segmentation method and an object-extraction procedure to extract the diatom from the background. First, we binarize the image by searching the optimal threshold in the histogram based on its cumulative distribution function. Then we eliminate, under some spatial cri…

Mammographic images segmentation based on chaotic map clustering algorithm

2013

Background: This work investigates the applicability of a novel clustering approach to the segmentation of mammographic digital images. The chaotic map clustering algorithm is used to group together similar subsets of image pixels resulting in a medically meaningful partition of the mammography. Methods: The image is divided into pixels subsets characterized by a set of conveniently chosen features and each of the corresponding points in the feature space is associated to a map. A mutual coupling strength between the maps depending on the associated distance between feature space points is subsequently introduced. On the system of maps, the simulated evolution through chaotic dynamics leads…

A system for sign language sentence recognition based on common sense context

2005

The paper proposes a complete framework for sign language recognition that integrates common sense in order to deal with sentences. The proposed system is based on a cognitive architecture allows modeling and managing the knowledge of the recognition process in a simple and robust way. The final abstraction level of this architecture introduces the semantic context and the analysis of the correctness of a sentence given a sequence of recognized signs. Experimentations are presented using the Italian sign language (LIS), and shows that the system maintains the recognition rate high when set of sign grows, correcting erroneous recognized single sign using the context

Valutazione quantitativa tridimensionale del parenchima polmonare affetto da fibrosi cistica : risultati preliminari

2007

Purpose. The aim of this study was to assess the feasibility of three-dimensional (3D) reconstructions and quantitative analysis of the volume of each component of the lung with cystic fibrosis (CF). Materials and methods. Twenty-two patients with CF (mean age 17±8 yeas) were included in the study. The patients underwent an unenhanced single-slice spiral computed tomography (CT) chest scan with the following parameters: collimation 3 mm, table feed 6 mm×rot-1, reconstruction interval 1 mm, soft tissue reconstruction kernel. Four image data sets were obtained: native axial slices, cine-mode display, virtual bronchographic volumerendered images with algorithm for tissue transition display and…