0000000000014394
AUTHOR
Cesare Valenti
Two-view “cylindrical decomposition” of binary images
This paper describes the discrete cylindrical algebraic decomposition (DCAD) construction along two orthogonal views of binary images. The combination of two information is used to avoid ambiguities for image recognition purposes. This algorithm associates an object connectivity graph to each connected component, allowing a complete description of the structuring information. Moreover, an easy and compact representation of the scene is achieved by using strings in a five letter alphabet. Examples on complex digital images are also provided. © 2001 Elsevier Science Inc.
Edge-Based Missing Data Imputation in Large-Scale Environments
Smart cities leverage large amounts of data acquired in the urban environment in the context of decision support tools. These tools enable monitoring the environment to improve the quality of services offered to citizens. The increasing diffusion of personal Internet of things devices capable of sensing the physical environment allows for low-cost solutions to acquire a large amount of information within the urban environment. On the one hand, the use of mobile and intermittent sensors implies new scenarios of large-scale data analysis
Representing 2D Digital Objects
The paper describes the combination a multi-views approach to represent connected components of 2D binary images. The approach is based on the Object Connectivity Graph (OCG), which is a sub-graph of the connectivity graph generated by the Discrete Cylindrical Algebraic Decomposition(DCAD) performed in the 2D discrete space. This construction allows us to find the number of connected components, to determine their connectivity degree, and to solve visibility problem. We show that the CAD construction, when performed on two orthogonal views, supply information to avoid ambiguities in the interpretation of each image component. The implementation of the algorithm is outlined and the computati…
Approximated overlap error for the evaluation of feature descriptors on 3D scenes
This paper presents a new framework to evaluate feature descriptors on 3D datasets. The proposed method employs the approximated overlap error in order to conform with the reference planar evaluation case of the Oxford dataset based on the overlap error. The method takes into account not only the keypoint centre but also the feature shape and it does not require complex data setups, depth maps or an accurate camera calibration. Only a ground-truth fundamental matrix should be computed, so that the dataset can be freely extended by adding further images. The proposed approach is robust to false positives occurring in the evaluation process, which do not introduce any relevant changes in the …
A memetic approach to discrete tomography from noisy projections
Discrete tomography deals with the reconstruction of images from very few projections, which is, in the general case, an NP-hard problem. This paper describes a new memetic reconstruction algorithm. It generates a set of initial images by network flows, related to two of the input projections, and lets them evolve towards a possible solution, by using crossover and mutation. Switch and compactness operators improve the quality of the reconstructed images during each generation, while the selection of the best images addresses the evolution to an optimal result. One of the most important issues in discrete tomography is known as the stability problem and it is tackled here, in the case of no…
An Island Strategy for Memetic Discrete Tomography Reconstruction
In this paper we present a parallel island model memetic algorithm for binary discrete tomography reconstruction that uses only four projections without any further a priori information. The underlying combination strategy consists in separated populations of agents that evolve by means of different processes. Agents progress towards a possible solution by using genetic operators, switch and a particular compactness operator. A guided migration scheme is applied to select suitable migrants by considering both their own and their sub-population fitness. That is, from time to time, we allow some individuals to transfer to different subpopulations. The benefits of this paradigm were tested in …
LinguAPP: An m-Health Application for Teledentistry Diagnostics
An Android/iOS application for low-cost mobile devices to aid in dental diagnosis through questionnaire and photos is presented in this paper. The main purposes of our app lie in the ease of use even for nonexperienced users, in the limited hardware requirements that allow a wide diffusion, and in the possibility to modify the questionnaire for different pathologies. This tool was developed in about a month at the beginning of the COVID-19 (SARS-CoV-2) pandemic and is still in use in Italy to allow support to patients without going to the hospital, if not strictly necessary.
A system for the automatic measurement of the nuchal translucency thickness from ultrasound video stream of the foetus
Nowadays the measurement of the nuchal translucency thickness is being used as part of routine ultrasound scanning during the end of the first trimester of pregnancy, for the screening of chromosomal defects, as trisomy 21. Currently, the measurement is being performed manually by physicians. The measurement can take a long time for being accomplished, needs to be performed by highly skilled operators, and is prone to errors. Semi-automated methods requires that the user manually selects a region of the image containing the nuchal translucency, procedure that is somewhat time consuming. In this paper we present a complete system prototype that is able to perform the measurement of the nucha…
A non-parametric Scale-based Corner Detector
This paper introduces a new Harris-affine corner detector algorithm, that does not need parameters to locate corners in images, given an observation scale. Standard detectors require to fine tune the values of parameters which strictly depend on the particular input image. A quantitative comparison between our implementation and a standard Harris-affine implementation provides good results, showing that the proposed methodology is robust and accurate. The benchmark consists of public images used in literature for feature detection.
A genetic approach to the maximum common subgraph problem
Finding the maximum common subgraph of a pair of given graphs is a well-known task in theoretical computer science and with considerable practical applications, for example, in the fields of bioinformatics, medicine, chemistry, electronic design and computer vision. This problem is particularly complex and therefore fast heuristics are required to calculate approximate solutions. This article deals with a simple yet effective genetic algorithm that finds quickly a solution, subject to possible geometric constraints.
Shape-Based Features for Cat Ganglion Retinal Cells Classification
This article presents a quantitative and objective approach to cat ganglion cell characterization and classification. The combination of several biologically relevant features such as diameter, eccentricity, fractal dimension, influence histogram, influence area, convex hull area, and convex hull diameter are derived from geometrical transforms and then processed by three different clustering methods (Ward’s hierarchical scheme, K-means and genetic algorithm), whose results are then combined by a voting strategy. These experiments indicate the superiority of some features and also suggest some possible biological implications.
Exudates as Landmarks Identified through FCM Clustering in Retinal Images
The aim of this work was to develop a method for the automatic identification of exudates, using an unsupervised clustering approach. The ability to classify each pixel as belonging to an eventual exudate, as a warning of disease, allows for the tracking of a patient&rsquo
Symmetry operators in computer vision
Abstract Symmetry plays a remarkable role in perception problems. For example, peaks of brain activity are measured in correspondence with visual patterns showing symmetry . Relevance of symmetry in vision was already noted by Koler in 1929. Here, properties of a symmetry operator are reported and a new algorithm to measure local symmetries is proposed. Its performance is tested on segmentation of complex visual patterns and the classification of sparse images.
Genetic Normalized Convolution
Normalized convolution techniques operate on very few samples of a given digital signal and add missing information, trough spatial interpolation. From a practical viewpoint, they make use of data really available and approximate the assumed values of the missing information. The quality of the final result is generally better than that obtained by traditional filling methods as, for example, bilinear or bicubic interpolations. Usually, the position of the samples is assumed to be random and due to transmission errors of the signal. Vice versa, we want to apply normalized convolution to compress data. In this case, we need to arrange a higher density of samples in proximity of zones which c…
Discrete Tomography Reconstruction Through a New Memetic Algorithm
Discrete tomography is a particular case of computerized tomography that deals with the reconstruction of objects made of just one homogeneous material, where it is sometimes possible to reduce the number of projections to no more than four. Most methods for standard computerized tomography cannot be applied in the former case and ad hoc techniques must be developed to handle so few projections.
Intra-tumor heterogeneity of Diffuse Large B-cell Lymphoma involves the induction of diversified stroma-tumor interfaces
ABSTRACTIntra-tumor heterogeneity in lymphoid malignancies is articulated around several fundamentals, encompassing selection of genetic subclonal events and epigenetic regulation of transcriptional programs. Clonally-related neoplastic cell populations are unsteadily subjected to immune editing and metabolic adaptations within different tissue microenvironments. How tissue-intrinsic mesenchymal determinants impact on the diversification of aggressive lymphomas is still unknown. In this study we adopted the established A20 line-based model of Diffuse Large B-cell Lymphoma (DLBCL), to investigate the intra-tumor heterogeneity associated with the infiltration of different tissue microenvironm…
A REST-based framework to support non-invasive and early coeliac disease diagnosis
The health sector has traditionally been one of the early adopters of databases, from the most simple Electronic Health Record (formerly Computer-Based Patient Record) systems in use in general practice, hospitals and intensive care units to big data, multidata based systems used to support diagnosis and care decisions. In this paper we present a framework to support non-invasive and early diagnosis of coeliac disease. The proposed framework makes use of well-known technologies and techniques, both hardware and software, put together in a novel way. The main goals of our framework are: (1) providing users with a reliable and fast repository of a large amount of data; (2) to make such reposi…
Estimating Missing Information by Cluster Analysis and Normalized Convolution
International audience; Smart city deals with the improvement of their citizens' quality of life. Numerous ad-hoc sensors need to be deployed to know humans' activities as well as the conditions in which these actions take place. Even if these sensors are cheaper and cheaper, their installation and maintenance cost increases rapidly with their number. We propose a methodology to limit the number of sensors to deploy by using a standard clustering technique and the normalized convolution to estimate environmental information whereas sensors are actually missing. In spite of its simplicity, our methodology lets us provide accurate assesses.
Semi-automatic registration of retinal images based on line matching approach
Accurate retinal image registration is essential to track the evolution of eye-related diseases. We propose a semiautomatic method based on features relying upon retinal graphs for temporal registration of retinal images. The features represent straight lines connecting vascular landmarks on the retina vascular tree: bifurcations, branchings, crossings, end points. In the built retinal graph, one straight line between two vascular landmarks indicates that they are connected by a vascular segment in the original retinal image. The locations of the landmarks are manually extracted to avoid the information loss due to errors in a retinal vessels segmentation algorithms. A straight line model i…
Visualization of Simulated Arrhythmias due to Gap Junctions
New computational models are able to simulate details of cardiac cell networks. Their results allow a better understanding of the functionality of the heart and suggest possible actions to reduce non-fatal premature beats that can give rise to serious diseases. We developed a user-friendly interface to organize Neuron simulations and to present in real-time a three-dimensional representation of the electrical activity due to the gap junctions which interconnect the cells inside cardiac tissues. All physiological parameters were set according to real experimental observations and compared against different types of arrhythmias, retrieved from the Physionet Data Base.
Neutrophil extracellular traps arm DC vaccination against NPM-mutant myeloproliferation
Neutrophil extracellular traps (NETs) are web-like chromatin structures composed by dsDNA and histones, decorated with antimicrobial proteins. Their interaction with dendritic cells (DCs) allows DC activation and maturation toward presentation of NET-associated antigens. Differently from other types of cell death that imply protein denaturation, NETosis preserves the proteins localized onto the DNA threads for proper enzymatic activity and conformational status, including immunogenic epitopes. Besides neutrophils, leukemic cells can release extracellular traps displaying leukemia-associated antigens, prototypically mutant nucleophosmin (NPMc+) that upon mutation translocates from nucleolus …
A cooperating strategy for objects recognition
The paper describes an object recognition system, based on the co-operation of several visual modules (early vision, object detector, and object recognizer). The system is active because the behavior of each module is tuned on the results given by other modules and by the internal models. This solution allows to detect inconsistencies and to generate a feedback process. The proposed strategy has shown good performance especially in case of complex scene analysis, and it has been included in the visual system of the DAISY robotics system. Experimental results on real data are also reported.
A non-parametric segmentation methodology for oral videocapillaroscopic images
We aim to describe a new non-parametric methodology to support the clinician during the diagnostic process of oral videocapillaroscopy to evaluate peripheral microcirculation. Our methodology, mainly based on wavelet analysis and mathematical morphology to preprocess the images, segments them by minimizing the within-class luminosity variance of both capillaries and background. Experiments were carried out on a set of real microphotographs to validate this approach versus handmade segmentations provided by physicians. By using a leave-one-patient-out approach, we pointed out that our methodology is robust, according to precision-recall criteria (average precision and recall are equal to 0.9…
Keypoint descriptor matching with context-based orientation estimation
Abstract This paper presents a matching strategy to improve the discriminative power of histogram-based keypoint descriptors by constraining the range of allowable dominant orientations according to the context of the scene under observation. This can be done when the descriptor uses a circular grid and quantized orientation steps, by computing or providing a global reference orientation based on the feature matches. The proposed matching strategy is compared with the standard approaches used with the SIFT and GLOH descriptors and the recent rotation invariant MROGH and LIOP descriptors. A new evaluation protocol based on an approximated overlap error is presented to provide an effective an…
Intra-tumour heterogeneity of diffuse large B-cell lymphoma involves the induction of diversified stroma-tumour interfaces
Abstract Background Intra-tumour heterogeneity in lymphoid malignancies encompasses selection of genetic events and epigenetic regulation of transcriptional programs. Clonal-related neoplastic cell populations are unsteadily subjected to immune editing and metabolic adaptations within different tissue microenvironments. How tissue-specific mesenchymal cells impact on the diversification of aggressive lymphoma clones is still unknown. Methods Combining in situ quantitative immunophenotypical analyses and RNA sequencing we investigated the intra-tumour heterogeneity and the specific mesenchymal modifications that are associated with A20 diffuse large B-cell lymphoma (DLBCL) cells seeding of d…
A fast recursive algorithm for the computation of axial moments
This paper describes a fast algorithm to compute local axial moments used for the detection of objects of interest in images. The basic idea is grounded on the elimination of redundant operations while computing axial moments for two neighboring angles of orientation. The main result is that the complexity of recursive computation of axial moments becomes independent of the total number of computed moments in a given point, i.e. it is of the order O(N) where N is the data size. This result is of great importance in computer vision since many feature extraction methods are based on the computation of axial moments. The experimental results confirm the time complexity and accuracy predicted b…
Improving Harris corner selection strategy
This study describes a corner selection strategy based on the Harris approach. Corners are usually defined as interest points for which intensity variation in the principal directions is locally maximised, as response from a filter given by the linear combination of the determinant and the trace of the autocorrelation matrix. The Harris corner detector, in its original definition, is only rotationally invariant, but scale-invariant and affine-covariant extensions have been developed. As one of the main drawbacks, corner detector performances are influenced by two user-given parameters: the linear combination coefficient and the response filter threshold. The main idea of the authors' approa…
Retinal image synthesis through the least action principle
Eye fundus image analysis is a fundamental approach in medical diagnosis and follow-up ophthalmic diagnostics. Manual annotation by experts needs hard work, thus only a small set of annotated vessel structures is available. Examples such as DRIVE and STARE include small sets for training images of fundus image benchmarks. Moreover, there is no vessel structure annotation for a number of fundus image datasets. Synthetic images have been generated by using appropriate parameters for the modeling of vascular networks or by methods developing deep learning techniques and supported by performance hardware. Our methodology aims to produce high-resolution synthetic fundus images alternative to the…
Prey-predator strategies in a multiagent system
This paper describes the prey-predator multiagent system which can be considered as an abstraction of more complex real-world models. Both the prey and the predators are considered as autonomous agents with their own behaviors and perception of the environment. In particular, we propose a simulator which lets study different strategies such as cooperation and individualism. An extensive experiment has been carried out in order to prove the effectiveness of the latter.
A Memetic Island Model for Discrete Tomography Reconstruction
Soft computing is a term indicating a coalition of methodologies, and its basic dogma is that, in general, better results can be obtained through the use of constituent methodologies in combination, rather than in a stand alone mode. Evolutionary computing belongs to this coalition, and thus memetic algorithms. Here, we present a combination of several instances of a recently proposed memetic algorithm for discrete tomography reconstruction, based on the island model parallel implementation. The combination is motivated by the fact that, even though the results of the recently proposed approach are finally better and more robust compared to other approaches, we advised that its major drawba…
Sparse Distributed Representation of Odors in a Large-scale Olfactory Bulb Circuit
In the olfactory bulb, lateral inhibition mediated by granule cells has been suggested to modulate the timing of mitral cell firing, thereby shaping the representation of input odorants. Current experimental techniques, however, do not enable a clear study of how the mitral-granule cell network sculpts odor inputs to represent odor information spatially and temporally. To address this critical step in the neural basis of odor recognition, we built a biophysical network model of mitral and granule cells, corresponding to 1/100th of the real system in the rat, and used direct experimental imaging data of glomeruli activated by various odors. The model allows the systematic investigation and g…
Classification of cat ganglion retinal cells and implications for shape-function relationship
This article presents a quantitative approach to ganglion cell classification by considering combinations of several geometrical features including fractal dimension, symmetry, diameter, eccentricity and convex hull. Special attention is given to moment and symmetry-based features. Several combinations of such features are fed to two clustering methods (Ward's hierarchical scheme and K-Means) and the respectively obtained classifications are compared. The results indicate the superiority of some features, also suggesting possible biological implications.
A Memetic Algorithm for Binary Image Reconstruction
This paper deals with a memetic algorithm for the reconstruction of binary images, by using their projections along four directions. The algorithm generates by network flows a set of initial images according to two of the input projections and lets them evolve toward a solution that can be optimal or close to the optimum. Switch and compactness operators improve the quality of the reconstructed images which belong to a given generation, while the selection of the best image addresses the evolution to an optimal output.
Evaluation of the Oral Microcirculation in Patients Undergoing Anti COVID-19 Vaccination: A Preliminary Study
Videocapillaroscopy allows the study of both the morphological and architectural structure of the microcirculation and its hemodynamic conditions; these parameters are directly involved in autoimmune and/or inflammatory pathologies. The purpose of this research, based on capillaroscopy, is to establish whether a patient who receives an anti-COVID 19 vaccine has any changes in their oral microcirculation. A complete capillaroscopic mapping of the oral cavity of the subjects examined was made; the investigated mucosa sites were the following: cheek, labial, chewing-gingival and back of the tongue. This study showed an increase in capillary density from the comparison between the mean labial c…
Trabectedin Overrides Osteosarcoma Differentiative Block and Reprograms the Tumor Immune Environment Enabling Effective Combination with Immune Checkpoint Inhibitors.
Abstract Purpose: Osteosarcoma, the most common primary bone tumor, is characterized by an aggressive behavior with high tendency to develop lung metastases as well as by multiple genetic aberrations that have hindered the development of targeted therapies. New therapeutic approaches are urgently needed; however, novel combinations with immunotherapies and checkpoint inhibitors require suitable preclinical models with intact immune systems to be properly tested. Experimental Design: We have developed immunocompetent osteosarcoma models that grow orthotopically in the bone and spontaneously metastasize to the lungs, mimicking human osteosarcoma. These models have been used to test the effica…
Unsupervised recognition of retinal vascular junction points.
Landmark points in retinal images can be used to create a graph representation to understand and to diagnose not only different pathologies of the eye, but also a variety of more general diseases. Aim of this paper is the description of a non-supervised methodology to distinguish between bifurcations and crossings of the retinal vessels, which can be used in differentiating between arteries and veins. A thinned representation of the binarized image, is used to identify pixels with three or more neighbors. Junction points are classified into bifurcations or crossovers according to their geometrical and topological properties. The proposed approach is successfully compared with the state-of-t…
An automated image analysis methodology for classifying megakaryocytes in chronic myeloproliferative disorders
This work describes an automatic method for discrimination in microphotographs between normal and pathological human megakaryocytes and between two kinds of disorders of these cells. A segmentation procedure has been developed, mainly based on mathematical morphology and wavelet transform, to isolate the cells. The features of each megakaryocyte (e.g. area, perimeter and tortuosity of the cell and its nucleus, and shape complexity via elliptic Fourier transform) are used by a regression tree procedure applied twice: the first time to find the set of normal megakaryocytes and the second to distinguish between the pathologies. The output of our classifier has been compared to the interpretati…
A genetic algorithm for discrete tomography reconstruction
The aim of this paper is the description of an experiment carried out to verify the robustness of two different approaches for the reconstruction of convex polyominoes in discrete tomography. This is a new field of research, because it differs from classic computerized tomography, and several problems are still open. In particular, the stability problem is tackled by using both a modified version of a known algorithm and a new genetic approach. The effect of both, instrumental and quantization noises has been considered too. © 2007 Springer Science+Business Media, LLC.
Local operators to detect regions of interest
The performance of a visual system is strongly influenced by the information processing that is done in the early vision phase. The need exists to limit the computation on areas of interest to reduce the total amount of data and their redundancy. This paper describes a new method to drive the attention during the analysis of complex scenes. Two new local operators, based on the computation of local moments and symmetries, are combined to drive the selection. Experimental results on real data are also reported. © 1997 Elsevier Science B.V.
Videocapillaroscopy of the Oral Mucosa in Patients with Diabetic Foot: Possible Diagnostic Role of Microangiopathic Damage?
Introduction: Diabetic foot represents one of the most serious and expensive complications of diabetes and is subject to a high percentage of amputations that are almost always preceded by ulcers ascribable to neuropathy and/or vasculopathy. Videocapillaroscopy (VCS) can be a valuable aid in order to uncover morpho-structural anomalies in the vascular bed, both at the level of the oral mucosa and at the level of the terminal vessels of the lower limb. Materials and methods: Sixty subjects divided into 4 groups were enrolled: 15 healthy subjects; 15 patients with diabetes for more than 10 years without ulcerative foot lesions; 15 patients with neuropathic diabetic foot (clinical diagnosis, M…
Cartoon filter via adaptive abstraction
We propose a non-parametric methodology to realize abstraction images.The redundant wavelet "a trous" algorithm is applied for details detection.An multi-scale circular median filter is used as a smoothing filter.The proposed algorithm is simple and fast on low-cost entry-level hardware. Abstraction in computer graphics defines a procedure that discriminates the essential information that is worth keeping. Usually details, that correspond to higher frequency components, allow to distinguish otherwise similar images. Vice versa, low frequencies are related to the main information, which are larger structures. Contours themselves may also be identified by high frequencies and separate each pi…
Flow evaluation of red blood cells in capillaroscopic videos
We aim at describing a non-parametric approach to evaluate blood cells velocity in oral capillascopic videos. The proposed methodology is based on the application of standard optical flow algorithms and it is part of a general environment to support during the diagnostic process for evaluating peripheral microcirculation in real time. We validated our approach versus handmade measurements provided by physicians. Results on real data pointed out that our system returns an output coherent to these latter observations.
Recognizing the Emergent and Submerged Iceberg of the Celiac Disease: ITAMA Project-Global Strategy Protocol.
Coeliac disease (CD) is frequently underdiagnosed with a consequent heavy burden in terms of morbidity and health care costs. Diagnosis of CD is based on the evaluation of symptoms and anti-transglutaminase antibodies IgA (TGA-IgA) levels, with values above a tenfold increase being the basis of the biopsy-free diagnostic approach suggested by present guidelines. This study showcased the largest screening project for CD carried out to date in school children (n=20,000) aimed at assessing the diagnostic accuracy of minimally invasive finger prick point-of-care tests (POCT) which, combined with conventional celiac serology and the aid of an artificial intelligence-based system, may eliminate t…
Evaluating Correlations in IoT Sensors for Smart Buildings
International audience; In this paper we introduce a dataset of environmental information obtained via indoor and outdoor sensors deployed in the SMART Infrastructure Facility of the University of Wollongong (Australia). The acquired dataset is also made open-sourced along with this paper. We also propose a novel approach based on an evolutionary algorithm to determine pairs of correlated sensors. We compare our approach with three other standard techniques on the same dataset: on average, the accuracy of the evolutionary method is about 62,92%. We also evaluate the computational time, assessing the suitability of the proposed pipeline for real-time applications.
Image Segmentation Techniques for Healthcare Systems
The present special issue of the Journal of Healthcare Engineering collects articles written by researchers scattered around the world who belong to the academic and industrial environments. The papers of this special issue have been selected by a rigorous peer-reviewing process with the support of at least two reviewers per paper, along with the opinion written in the final decision by a component of the editorial staff. Different methods on biomedical image segmentation dedicated to healthcare systems have been developed regarding, for example, the fields of machine learning, deformable models, fuzzy models, and so on. Such methods have been applied on different biomedical image modalitie…
A naive approach to compose aerial images in a mosaic fashion
There is growing interest in multiple sequence image analysis to represent those data in a new landscape, for instance reconstruction of old films, mosaicing of images. This paper focuses attention on the mosaic problem; it introduces a naive method to link together images where a common part of the scene is present among two images. An application has been developed to test the method on aerial sequences of images. Given the long distance of aircraft from the scene, the method assumes images without distortions and without problems of prospective. Moreover, the application does not need any additional parameters coming from human experience and for this reason it can be thought of as a ful…
A non-supervised approach to locate and to measure the nuchal translucency by means of wavelet analysis and neural networks
Ultrasound imaging is a well known noninvasive way to evaluate various diseases during the prenatal age. In particular, the thickness measure of the nuchal transucency is strictly correlated with pathologies like trisomy 13, 18 and 21. For a correct investigation, the methodology needs mid-sagittal sections and the proposed approach is based on wavelet analysis and neural network classifiers to locate components useful to identify mid-sagittal planes. To evaluate the performance and the robustness of the methodology, real clinical ultrasound images were considered, obtaining an average error of at most 0.3 millimeters in 97.4% of the cases.
Segmentation and feature extraction in capillaroscopic videos
This contribution describes a method to select regions of interest as capillaries of the oral mucosa and to extract their main features useful for real diagnosis purposes. A discrete version of the wavelet transform has been adopted for segmenting the images coming from video sequences acquired by a prototype capillaroscopic, able to put in evidence the red blood flow. A set of proper characteristics is automatically computed for a correct evaluation of the peripheral microcirculation.
The stability problem and noisy projections in discrete tomography
Abstract The new field of research of discrete tomography will be described in this paper. It differs from standard computerized tomography in the reduced number of projections. It needs ad hoc algorithms which usually are based on the definition of the model of the object to reconstruct. The main problems will be introduced and an experimental simulation will prove the robustness of a slightly modified version of a well known method for the reconstruction of binary planar convex sets, even in case of projections affected by error. To the best of our knowledge this is one of the first experimental study of the stability problem with a statistical approach. Prospective applications include c…
An Evolution of the Non-Parameter Harris Affine Corner Detector: A Distributed Approach
A parallel version of a new automatic Harris-based corner detector is presented. A scheduler to dynamically and homogeneously distribute high computational workload on heterogeneous parallel architectures such as Grid systems has been implemented to speedup the whole procedure. Experimental results show the robustness of the underlying scheduler, which can be easily exploited in various automatic image analysis systems.
Complex objects classified by morphological shape analysis and elliptical Fourier descriptors
This chapter deals with the classification of complex objects by morphological shape analysis and elliptical Fourier descriptors. An unsupervised method has been proposed to identify components with specific shapes by a simple edge detector and to classify them via the description of their contours. A particular application has been arranged in order to evaluate the goodness of this approach when discriminating between normal and pathological human megakaryocytes. Alterations in these cells can occur in many pathological processes and in such cases the pattern, size and shape of the cytoplasm and/or of the nucleus are extremely varied.
The prolyl-isomerase PIN1 is essential for nuclear Lamin-B structure and function and protects heterochromatin under mechanical stress.
Summary: Chromatin organization plays a crucial role in tissue homeostasis. Heterochromatin relaxation and consequent unscheduled mobilization of transposable elements (TEs) are emerging as key contributors of aging and aging-related pathologies, including Alzheimer’s disease (AD) and cancer. However, the mechanisms governing heterochromatin maintenance or its relaxation in pathological conditions remain poorly understood. Here we show that PIN1, the only phosphorylation-specific cis/trans prolyl isomerase, whose loss is associated with premature aging and AD, is essential to preserve heterochromatin. We demonstrate that this PIN1 function is conserved from Drosophila to humans and prevents…
An experimental study of the stability problem in discrete tomography
This paper introduces the topic of discrete tomography, briefly showing its main applications, algorithms and new prospects of research. It focuses on the still open problem of stability, facing it from an experimental point of view. In particular an extensive simulation lets verify the robustness of a well known reconstruction technique for binary convex objects, calculating the probability of finding solutions compatible with a given set of noisy projections. © 2005 Elsevier Ltd. All rights reserved.
Wavelet analysis and neural network classifiers to detect mid-sagittal sections for nuchal translucency measurement
We propose a methodology to support the physician in the automatic identification of mid-sagittal sections of the fetus in ultrasound videos acquired during the first trimester of pregnancy. A good mid-sagittal section is a key requirement to make the correct measurement of nuchal translucency which is one of the main marker for screening of chromosomal defects such as trisomy 13, 18 and 21. NT measurement is beyond the scope of this article. The proposed methodology is mainly based on wavelet analysis and neural network classifiers to detect the jawbone and on radial symmetry analysis to detect the choroid plexus. Those steps allow to identify the frames which represent correct mid-sagitta…
Morphological Analysis Combined with a Machine Learning Approach to Detect Utrasound Median Sagittal Sections for the Nuchal Translucency Measurement
The screening of chromosomal defects, as trisomy 13, 18 and 21, can be obtained by the measurement of the nuchal translucency thickness scanning during the end of the first trimester of pregnancy. This contribution proposes an automatic methodology to detect mid-sagittal sections to identify the correct measurement of nuchal translucency. Wavelet analysis and neural network classifiers are the main strategies of the proposed methodology to detect the frontal components of the skull and the choroid plexus with the support of radial symmetry analysis. Real clinical ultrasound images were adopted to measure the performance and the robustness of the methodology, thus it can be highlighted an er…
Content Based Indexing of Image and Video Databases by Global and Shape Features
Indexing and retrieval methods based on the image content are required to effectively use information from the large repositories of digital images and videos currently available. Both global (colour, texture, motion, etc.) and local (object shape, etc.) features are needed to perform a reliable content based retrieval. We present a method for automatic extraction of global image features, like colour and motion parameters, and their use for data restriction in video database querying. Further retrieval is therefore accomplished, in a restricted set of images, by shape feature (skeleton, local symmetry moments, correlation, etc.) local search. The proposed indexing methodology has been deve…
Automatic detection and measurement of nuchal translucency.
In this paper we propose a new methodology to support the physician both to identify automatically the nuchal region and to obtain a correct thickness measurement of the nuchal translucency. The thickness of the nuchal translucency is one of the main markers for screening of chromosomal defects such as trisomy 13, 18 and 21. Its measurement is performed during ultrasound scanning in the first trimester of pregnancy. The proposed methodology is mainly based on wavelet and multi resolution analysis. The performance of our method was analysed on 382 random frames, representing mid-sagittal sections, uniformly extracted from real clinical ultrasound videos of 12 patients. According to the groun…
A Fast Multiresolution Approach Useful for Retinal Image Segmentation
Retinal diseases such as retinopathy of prematurity (ROP), diabetic and hypertensive retinopathy present several deformities of fundus oculi which can be analyzed both during screening and monitoring such as the increase of tortuosity, lesions of tissues, exudates and hemorrhages. In particular, one of the first morphological changes of vessel structures is the increase of tortuosity. The aim of this work is the enhancement and the detection of the principal characteristics in retinal image by exploiting a non-supervised and automated methodology. With respect to the well-known image analysis through Gabor or Gaussian filters, our approach uses a filter bank that resembles the “à trous” wav…
An Automatic Three-Dimensional Fuzzy Edge Detector
Three-dimensional object analysis is of particular interest in many research fields. In this context, the most common data representation is boundary mesh, namely, 2D surface embedded in 3D space. We will investigate the problem of 3D edge extraction, that is, salient surface regions characterized by high flexure. Our automatic edge detection method assigns a value, proportional to the local bending of the surface, to the elements of the mesh. Moreover, a proper scanning window, centered on each element, is used to discriminate between smooth zones of the surface and its edges. The algorithm does not require input parameters and returns a set of elements that represent the salient features …
Automatic detection and classification of retinal vascular landmarks
The main contribution of this paper is introducing a method to distinguish between different landmarks of the retina: bifurcations and crossings. The methodology may help in differentiating between arteries and veins and is useful in identifying diseases and other special pathologies, too. The method does not need any special skills, thus it can be assimilated to an automatic way for pinpointing landmarks; moreover it gives good responses for very small vessels. A skeletonized representation, taken out from the segmented binary image (obtained through a preprocessing step), is used to identify pixels with three or more neighbors. Then, the junction points are classified into bifurcations or…
Filter Bank: a Directional Approach for Retinal Vessel Segmentation
It is well known that retinal diseases are sometimes identified by tortuosity of the vessels, presence of exudates and hemorrhages while lesions of tissues are associated to diabetic retinopathy, retinopathy of prematurity and more general cerebrovascular problems. One of the main issues in this research field is detecting small curvilinear structures, thus the aim of this contribution is to introduce a non-supervised and automated methodology to detect features such as curvilinear structures in retinal images. The core of the proposed methodology consists in using an approach that resembles the “a trous” wavelet algorithm. With respect to the standard Gabor analysis our methodology is base…