Search results for "Active contour"
showing 10 items of 20 documents
Active contour algorithm with discriminant analysis for delineating tumors in positron emission tomography.
2019
Abstract In the context of cancer delineation using positron emission tomography datasets, we present an innovative approach which purpose is to tackle the real-time, three-dimensional segmentation task in a full, or at least nearly full automatized way. The approach comprises a preliminary initialization phase where the user highlights a region of interest around the cancer on just one slice of the tomographic dataset. The algorithm takes care of identifying an optimal and user-independent region of interest around the anomalous tissue and located on the slice containing the highest standardized uptake value so to start the successive segmentation task. The three-dimensional volume is then…
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…
IMAGE PROCESSING, SEGMENTATION AND MACHINE LEARNING MODELS TO CLASSIFY AND DELINEATE TUMOR VOLUMES TO SUPPORT MEDICAL DECISION
2020
Techniques for processing and analysing images and medical data have become the main’s translational applications and researches in clinical and pre-clinical environments. The advantages of these techniques are the improvement of diagnosis accuracy and the assessment of treatment response by means of quantitative biomarkers in an efficient way. In the era of the personalized medicine, an early and efficacy prediction of therapy response in patients is still a critical issue. In radiation therapy planning, Magnetic Resonance Imaging (MRI) provides high quality detailed images and excellent soft-tissue contrast, while Computerized Tomography (CT) images provides attenuation maps and very good…
<title>Restoration of a short-exposure image sequence degraded by atmospheric turbulence</title>
2000
This paper deals with the restoration of the shape of an object observed with a high-resolution infrared imaging device, through atmospheric turbulence. The propagation path is quite long (a few tenth kilometer) and the image is thus disturbed. A sequence of short-exposure images of the interesting object is recorded. We can see that the object shape fluctuates randomly during the sequence, but that its edges remain sharp, thanks to the very short exposure time. A bayesian analysis of the Fourier descriptors associated to the edges shows that the optimal shape is the one corresponding to the mean Fourier descriptors. We thus propose two ways to estimate this shape. The first one consists in…
A novel active contour model for unsupervised low-key image segmentation
2013
Published version of an article in the journal: Central European Journal of Engineering. Also available from the publisher at: http://dx.doi.org/10.2478/s13531-012-0050-0 Unsupervised image segmentation is greatly useful in many vision-based applications. In this paper, we aim at the unsupervised low-key image segmentation. In low-key images, dark tone dominates the background, and gray level distribution of the foreground is heterogeneous. They widely exist in the areas of space exploration, machine vision, medical imaging, etc. In our algorithm, a novel active contour model with the probability density function of gamma distribution is proposed. The flexible gamma distribution gives a bet…
Definition of a mutual reference shape based on information theory and active contours
2013
In this paper, we propose to consider the estimation of a reference shape from a set of different segmentation results using both active contours and information theory. The reference shape is then defined as the minimum of a criterion that benefits from both the mutual information and the joint entropy of the input segmentations. This energy criterion is here justified using similarities between information theory quantities and area measures, and presented in a continuous variational framework. This framework brings out some interesting evaluation measures such as the specificity and sensitivity. In order to solve this shape optimization problem, shape derivatives are computed for each te…
Automatic analyzis of droplet impact by high speed imaging
2012
International audience; The impact of agricultural activities on the water quality is the consequence of the loss of fertilisers (chemical fertilisers, livestock effluent, also referred to as farm fertiliser, food-processing effluent and sludge) and crop treatment products (phytosanitary products). This pollution may prevent certain uses of water, notably its use for human and animal food (groundwater and surface water), and leads to a deterioration in aquatic environments. In the domain of vineyard precision spraying research, one of the most important objectives is to minimize the volume of phytosanitary products. It is also to be more environmentally respectful with more effective vine l…
Primary ciliary dyskinesia assessment by means of optical flow analysis of phase-contrast microscopy images
2014
Primary ciliary dyskinesia implies cilia with defective or total absence of motility, which may result in sinusitis, chronic bronchitis, bronchiectasis and male infertility. Diagnosis can be difficult and is based on an abnormal ciliary beat frequency (CBF) and beat pattern. In this paper, we present a method to determine CBF of isolated cells through the analysis of phase-contrast microscopy images, estimating cilia motion by means of an optical flow algorithm. After having analyzed 28 image sequences (14 with a normal beat pattern and 14 with a dyskinetic pattern), the normal group presented a CBF of 5.2 +/- 1.6 Hz, while the dyskinetic patients presented a 1.9 +/- 0.9 Hz CBF. The cutoff …
Automatic detection of lung nodules in CT datasets based on stable 3D mass–spring models
2012
We propose a computer-aided detection (CAD) system which can detect small-sized (from 3 mm) pulmonary nodules in spiral CT scans. A pulmonary nodule is a small lesion in the lungs, round-shaped (parenchymal nodule) or worm-shaped (juxtapleural nodule). Both kinds of lesions have a radio-density greater than lung parenchyma, thus appearing white on the images. Lung nodules might indicate a lung cancer and their early stage detection arguably improves the patient survival rate. CT is considered to be the most accurate imaging modality for nodule detection. However, the large amount of data per examination makes the full analysis difficult, leading to omission of nodules by the radiologist. We…
A CAD system for nodule detection in low-dose lung CTs based on region growing and a new active contour model
2007
A computer-aided detection (CAD) system for the selection of lung nodules in computer tomography (CT) images is presented. The system is based on region growing (RG) algorithms and a new active contour model (ACM), implementing a local convex hull, able to draw the correct contour of the lung parenchyma and to include the pleural nodules. The CAD consists of three steps: (1) the lung parenchymal volume is segmented by means of a RG algorithm; the pleural nodules are included through the new ACM technique; (2) a RG algorithm is iteratively applied to the previously segmented volume in order to detect the candidate nodules; (3) a double-threshold cut and a neural network are applied to reduce…