Search results for "Segmentation"
showing 10 items of 674 documents
Identification of the most informative wavelengths for non-invasive melanoma diagnostics in spectral region from 450 to 950 nm
2020
In this study 300 skin lesion (including 32 skin melanomas) multispectral data cubes were analyzed. The multi-step and single step machine learning approaches were analyzed to find the wavebands that provide the most information that helps discriminate skin melanoma from other benign pigmented lesions. The multi-step machine learning approach assumed training several models but proved itself to be ineffective. The reason for that is a necessity to train a segmentation model on a very small dataset and utilization of standard machine learning classifier which have shown poor classification performance. The single-step approach is based on a deep learning neural network. We have conducted 260…
Análisis geodemográfico y planificación territorial en España
2002
This article studies the current role of geodemographic analysis in Spanish spatial planning; its importance, gaps and problems. This is done both from a theoretical and planning perspectives. The theoretical perspective studies the references to the population in the legal norm of the several forms of planning, and in particular in the very recent Autonomous Regions' laws. The planning perspective refers to the specific spatial plans that have been aproved. The article identifies three types of spatial planning: urban planning, town and country planning and environmental planning. Therefore, excluding the sectorial planning with spatial incidence.
Review on Machine Learning Based Lesion Segmentation Methods from Brain MR Images
2016
Brain lesions are life threatening diseases. Traditional diagnosis of brain lesions is performed visually by neuro-radiologists. Nowadays, advanced technologies and the progress in magnetic resonance imaging provide computer aided diagnosis using automated methods that can detect and segment abnormal regions from different medical images. Among several techniques, machine learning based methods are flexible and efficient. Therefore, in this paper, we present a review on techniques applied for detection and segmentation of brain lesions from magnetic resonance images with supervised and unsupervised machine learning techniques.
Image boundaries detection: from thresholding to implicit curve evolution
2014
The development of high dimensional large-scale imaging devices increases the need of fast, robust and accurate image segmentation methods. Due to its intrinsic advantages such as the ability to extract complex boundaries, while handling topological changes automatically, the level set method (LSM) has been widely used in boundaries detection. Nevertheless, their computational complexity limits their use for real time systems. Furthermore, most of the LSMs share the limit of leading very often to a local minimum, while the effectiveness of many computer vision applications depends on the whole image boundaries. In this paper, using the image thresholding and the implicit curve evolution fra…
Architecture-Driven Level Set Optimization: From Clustering to Sub-pixel Image Segmentation
2016
Thanks to their effectiveness, active contour models (ACMs) are of great interest for computer vision scientists. The level set methods (LSMs) refer to the class of geometric active contours. Comparing with the other ACMs, in addition to subpixel accuracy, it has the intrinsic ability to automatically handle topological changes. Nevertheless, the LSMs are computationally expensive. A solution for their time consumption problem can be hardware acceleration using some massively parallel devices such as graphics processing units (GPUs). But the question is: which accuracy can we reach while still maintaining an adequate algorithm to massively parallel architecture? In this paper, we attempt to…
A local level set method for liver segmentation in functional MR imaging
2011
Functional Magnetic Resonance (fMR) is a medical image technique in which a contrast is injected in the vascular system so that blood diffusion along it can be observed as variations of the signal intensity. The uptake variations of the contrast agent are used in early detection of tumorous tissue. For the diagnostic to be accurate, successive volumes must be correctly registered. For binary registration prior segmentation of the 3D fMR data is required. Here we present a local 3D level-set segmentation method which preserves details and edges, along with its multi-scale version which has the advantage of a great acceleration with respect to the single-scale version. Results of liver segmen…
Efficacy of screen recording in the other-revision of translations: episodic memory and event models
2014
In a 2011 study, Angelone compared the self-revision results of graduate German translation students. Participants documented their original translations using Integrated Problem and Decision Reporting (IPDR) logs (Gile 2004), think-aloud protocols and screen recordings. They then used this documentation to assist self-revision of their translations. Angelone found a significant improvement in error detection overall and in each of six discrete error categories when participants used screen recordings to assist their self-revision. We sought to partially replicate Angelone’s findings concerning the efficacy of screen recording in translation revision. Instead of focusing on self-revision, w…
Les eines computacionals i el disseny de corpus orals: un diàleg vigent
2020
The design of an oral corpus and the processes of registering, codifying and treating the materials in order to build a useful resource for linguistic analysis prompt numerous decisions regarding theory and methodology. This article is focused on those stages of corpus construction which are more clearly conditioned by the computational processing necessary to make it functional. In order to adequately match the initial expectations and the real possibilities of using the tool, each feature we intend to codify must be measured against the workload and the means required to do so. Therefore, it is essential to take into account the available possibilities of processing and exploitation as th…
Complexity and interaction: comparing the development of L1 and L2
2011
In research into first and second language development, the focus has mainly been either on the formal features of learner language alone (both L1 and L2) or on the interaction between learners and their caretakers (L1) or native speaker peers (L2).These research traditions have been kept a part even though it has been widely acknowledged that both first and second languages are appropriated essentially in social interaction. This paper aims to strengthen the connection between social and formal approaches by combining interactional views with those focusing on the structural complexity of learner language. Some excerpts from L1 and L2 interaction data (in the Finnish language) are discusse…
Automatic segmentation and 3D reconstruction of intravascular ultrasound images for a fast preliminar evaluation of vessel pathologies.
2007
Abstract Intravascular ultrasound (IVUS) imaging is used along with X-ray coronary angiography to detect vessel pathologies. Manual analysis of IVUS images is slow and time-consuming and it is not feasible for clinical purposes. A semi-automated method is proposed to generate 3D reconstructions from IVUS video sequences, so that a fast diagnose can be easily done, quantifying plaque length and severity as well as plaque volume of the vessels under study. The methodology described in this work has four steps: a pre-processing of IVUS images, a segmentation of media–adventitia contour, a detection of intima and plaque and a 3D reconstruction of the vessel. Preprocessing is intended to remove …