Search results for "SEGMENTATION"
showing 10 items of 674 documents
Automatic Segmentation of HEp-2 Cells Based on Active Contours Model
2018
In the past years, a great deal of effort was put into research regarding Indirect Immunofluorescence techniques with the aim of development of CAD systems. In this work a method for segmenting HEp-2 cells in IIF images is presented. Such task is one of the most challenging of automated IIF analysis, because the segmentation algorithm has to cope with a large heterogeneity of shapes and textures. In order to address this problem, numerous techniques and their combinations were evaluated, in a process aimed at maximizing the figure of merit. The proposed method, for a greater definition of cellular contours, uses the active contours in the last phase of the process. The initial conditions, c…
253. An accurate and operator independent method for biological tumour volume segmentation
2018
Purpose The aim of this paper is to develop an operator independent method for biological tumour volume (BTV) delineation from Positron Emission Tomography (PET) images. BTV delineation is challenging because of the low spatial resolution and high noise level in PET images. In addition, BTV varies substantially depending on the method used to segment. Manual delineation is widely-used, but it is strongly user dependent. Methods The proposed method starts with the automatic identification of the PET slice with maximum Standardized Uptake Value (SUV). Then, a user- independent mask is obtained by a rough pre-segmentation step and it is used to perform the local active contour segmentation on …
Unsupervised low-key image segmentation using curve evolution approach
2013
Low-key images widely exist in imaging-based systems such as space telescopes, medical imaging equipment, machine vision systems. Unsupervised low-key image segmentation is an important process for image analysis or digital measurement in these applications. In this paper, a novel active contour model with the probability density function (PDF) of gamma distribution for image segmentation is proposed. The flexible gamma distribution is used to describe both of the heterogeneous foreground and dark background in a low-key image. Besides, an unsupervised curve initialization method is also designed in this paper, which helps to accelerate the convergence speed of curve evolution. The effectiv…
Remote sensing image segmentation by active queries
2012
Active learning deals with developing methods that select examples that may express data characteristics in a compact way. For remote sensing image segmentation, the selected samples are the most informative pixels in the image so that classifiers trained with reduced active datasets become faster and more robust. Strategies for intelligent sampling have been proposed with model-based heuristics aiming at the search of the most informative pixels to optimize model's performance. Unlike standard methods that concentrate on model optimization, here we propose a method inspired in the cluster assumption that holds in most of the remote sensing data. Starting from a complete hierarchical descri…
Adaptive Bias Field Correction: Application on Abdominal MR Images
2017
Segmentation of medical images is one of the most important phases for disease diagnosis. Accuracy, robustness and stability of the results obtained by image segmentation is a major concern. Many segmentation methods rely on absolute values of intensity level, which are affected by a bias term due to in-homogeneous field in magnetic resonance images. The main objective of this paper is two folded: (1) To show efficiency of an energy minimization based approach, which uses intrinsic component optimization, on abdominal magnetic resonance images. (2) To propose an adaptive method to stop the optimization automatically. The proposed method can control the value of the energy functional and sto…
Can colours be used to segment words when reading?
2015
Rayner, Fischer, and Pollatsek (1998, Vision Research) demonstrated that reading unspaced text in Indo-European languages produces a substantial reading cost in word identification (as deduced from an increased word-frequency effect on target words embedded in the unspaced vs. spaced sentences) and in eye movement guidance (as deduced from landing sites closer to the beginning of the words in unspaced sentences). However, the addition of spaces between words comes with a cost: nearby words may fall outside high-acuity central vision, thus reducing the potential benefits of parafoveal processing. In the present experiment, we introduced a salient visual cue intended to facilitate the process…
A semi-automatic approach for epicardial adipose tissue segmentation and quantification on cardiac CT scans
2019
Abstract Many studies have shown that epicardial fat is associated with a higher risk of heart diseases. Accurate epicardial adipose tissue quantification is still an open research issue. Considering that manual approaches are generally user-dependent and time-consuming, computer-assisted tools can considerably improve the result repeatability as well as reduce the time required for performing an accurate segmentation. Unfortunately, fully automatic strategies might not always identify the Region of Interest (ROI) correctly. Moreover, they could require user interaction for handling unexpected events. This paper proposes a semi-automatic method for Epicardial Fat Volume (EFV) segmentation a…
Towards a unified analysis of cerebellum maturation and aging across the entire lifespan: A MRI analysis
2021
[EN] Previous literature about the structural characterization of the human cerebellum is related to the context of a specific pathology or focused in a restricted age range. In fact, studies about the cerebellum maturation across the lifespan are scarce and most of them considered the cerebellum as a whole without investigating each lobule. This lack of study can be explained by the lack of both accurate segmentation methods and data availability. Fortunately, during the last years, several cerebellum segmenta- tion methods have been developed and many databases comprising subjects of dif- ferent ages have been made publically available. This fact opens an opportunity window to obtain a mo…
Speech- and sound-segmentation in dyslexia: evidence for a multiple-level cortical impairment
2006
Developmental dyslexia involves deficits in the visual and auditory domains, but is primarily characterized by an inability to translate the written linguistic code to the sound structure. Recent research has shown that auditory dysfunctions in dyslexia might originate from impairments in early pre-attentive processes, which affect behavioral discrimination. Previous studies have shown that whereas dyslexic individuals are deficient in discriminating sound distinctions involving consonants or simple pitch changes, discrimination of other sound aspects, such as tone duration, is intact. We hypothesized that such contrasts that can be discriminated by dyslexic individuals when heard in isolat…
pBrain: A novel pipeline for Parkinson related brain structure segmentation
2020
[EN] Parkinson is a very prevalent neurodegenerative disease impacting the life of millions of people worldwide. Although its cause remains unknown, its functional and structural analysis is fundamental to advance in the search of a cure or symptomatic treatment. The automatic segmentation of deep brain structures related to Parkinson's disease could be beneficial for the follow up and treatment planning. Unfortunately, there is not broadly available segmentation software to automatically measure Parkinson related structures. In this paper, we present a novel pipeline to segment three deep brain structures related to Parkinson's disease (substantia nigra, subthalamic nucleus and red nucleus…