Search results for "Segmentation"

A Multiresolution Approach Based on MRF and Bak–Sneppen Models for Image Segmentation

2006

The two major Markov Random Fields (MRF) based algorithms for image segmentation are the Simulated Annealing (SA) and Iterated Conditional Modes (ICM). In practice, compared to the SA, the ICM provides reasonable segmentation and shows robust behavior in most of the cases. However, the ICM strongly depends on the initialization phase. In this paper, we combine Bak-Sneppen model and Markov Random Fields to define a new image segmentation approach. We introduce a multiresolution technique in order to speed up the segmentation process and to improve the restoration process. Image pixels are viewed as lattice species of Bak-Sneppen model. The a-posteriori probability corresponds to a local fitn…

A Two Stage Neural Architecture for Segmentation and Superquadrics Recovery from Range Data

2002

A novel, two stage, neural architecture for the segmentation of range data and their modeling with undeformed superquadrics is presented. The system is composed by two distinct neural networks: a SOM is used to perform data segmentation, and, for each segment, a multilayer feed-forward network performs model estimation.

Metodi automatici di analisi e caratterizzazione di esami radiologici del massiccio facciale.

L'obiettivo di questo lavoro è lo sviluppo di algoritmi e procedure di analisi di referti radiografici digitali di tipo CBCT delle strutture della mandibola e dell’apparato dentario. In particolare, mediante un’opportuna campagna di sperimentazione, in collaborazione con i reparti di radiologia ed odontoiatria del Policlinico di Palermo, è stata realizzata un procedura in grado di: • eliminare i problemi di sovrapponibilità dei referti tridimensionali effettuati in tempi successivi; • identificare lo spazio parodontale su indagini CBCT per la valutazione dei possibili difetti nello stesso e prevedere l’insorgenza di parodontiti. • individuare gli elementi di maggiore interesse medico caratt…

Segmentation-Free Estimation of Aortic Diameters from MRI Using Deep Learning

2021

Accurate and reproducible measurements of the aortic diameters are crucial for the diagnosis of cardiovascular diseases and for therapeutic decision making. Currently, these measurements are manually performed by healthcare professionals, being time consuming, highly variable, and suffering from lack of reproducibility. In this work we propose a supervised deep-learning method for the direct estimation of aortic diameters. The approach is devised and tested over 100 magnetic resonance angiography scans without contrast agent. All data was expert-annotated at six aortic locations typically used in clinical practice. Our approach makes use of a 3D+2D convolutional neural network (CNN) that ta…

Microaneurysm detection with radon transform-based classification on retina images.

2012

The creation of an automatic diabetic retinopathy screening system using retina cameras is currently receiving considerable interest in the medical imaging community. The detection of microaneurysms is a key element in this effort. In this work, we propose a new microaneurysms segmentation technique based on a novel application of the radon transform, which is able to identify these lesions without any previous knowledge of the retina morphological features and with minimal image preprocessing. The algorithm has been evaluated on the Retinopathy Online Challenge public dataset, and its performance compares with the best current techniques. The performance is particularly good at low false p…

Exudate Segmentation on Retinal Atlas Space

2013

International audience; Diabetic macular edema is characterized by hard exudates. Presence of such exudates cause vision loss in the affected areas. We present a novel approach of segmenting exudates for screening and follow-ups by building an ethnicity based statistical atlas. The chromatic distribution in such an atlas gives a good measure of probability of the pixels belonging to the healthy retinal pigments or to the abnormalities (like lesions, imaging artifacts etc.) in the retinal fundus image. Post-processing schemes are introduced in this paper for the enhancement of the edges of such exudates for final segmentation and to separate lesion from false positives. A sensitivity(recall)…

A novel automated segmentation method for retinal layers in OCT images proves retinal degeneration after optic neuritis.

2015

Aim The evaluation of inner retinal layer thickness can serve as a direct biomarker for monitoring the course of inflammatory diseases of the central nervous system such as multiple sclerosis (MS). Using optical coherence tomography (OCT), thinning of the retinal nerve fibre layer and changes in deeper retinal layers have been observed in patients with MS. Here, we first compare a novel method for automated segmentation of OCT images with manual segmentation using two cohorts of patients with MS. Using this method, we also aimed to reproduce previous findings showing retinal degeneration following optic neuritis (ON) in MS. Methods Based on a 5×5 expansion of the Prewitt operator to efficie…

A Neural Architecture for Segmentation and Modelling of Range Data

2003

A novel, two stage, neural architecture for the segmentation of range data and their modeling with undeformed superquadrics is presented. The system is composed by two distinct neural stages: a SOM is used to perform data segmentation, and, for each segment, a multi-layer feed-forward network performs model estimation. The topology preserving nature of the SOM algorithm makes this architecture suited to cluster data with respect to sudden curvature variations. The second stage is designed to model and compute the inside-outside function of an undeformed superquadric in whatever attitude, starting form the (x, y, z) data triples. The network has been trained using backpropagation, and the we…

La segmentazione della domanda e dell’offerta nell’industria dell’ospitalità

2010

No two customers are identical, even whereas they belong to the same marketing program or they choose the same product or service (Withiam G., 2000). Revenues, costs and therefore profitability differ because of the different effort required to meet the specific need of the specific consumer or group of customers. When competing, firms target information towards specific segments through direct marketing initiatives and actions (Cross R.G., 1997). This finding underlines the importance of knowing in advance customer’s characteristics, even before thinking at the service to provide, and aims to illustrate how the lodging industry normally segments its customers, and which group of customers …

Semi-automatic Quasi-morphological Word Segmentation for Neural Machine Translation

2018

This paper proposes the Prefix-Root-Postfix-Encoding (PRPE) algorithm, which performs close-to-morphological segmentation of words as part of text pre-processing in machine translation. PRPE is a cross-language algorithm requiring only minor tweaking to adapt it for any particular language, a property which makes it potentially useful for morphologically rich languages with no morphological analysers available. As a key part of the proposed algorithm we introduce the ‘Root alignment’ principle to extract potential sub-words from a corpus, as well as a special technique for constructing words from potential sub-words. We conducted experiments with two different neural machine translation sys…