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Biomedical subjects

G Coppini

Publications and source records attributed to G Coppini.

18 recordsLinked to original sources
PubMed2004

Detection of single and clustered microcalcifications in mammograms using fractals models and neural networks.

Microcalcifications (microCas) are often early signs of breast cancer. However, detecting them is a difficult visual task and recognizing malignant lesions is a complex diagnostic problem. In recent years, several research groups have been working to develop computer-aided diagnosis (CAD) systems for X-ray mammography. In this paper, we propose a method to detect and classify microcalcifications. In order to discover the presence of microCas clusters, particular attention is paid to the analysis of the spatial arrangement of detected lesions. A fractal model has been used to describe the mammographic image, thus, allowing the use of a matched filtering stage to enhance microcalcifications against the background. A region growing algorithm, coupled with a neural classifier, detects existing lesions. Subsequently, a second fractal model is used to analyze their spatial arrangement so that the presence of microcalcification clusters can be detected and classified. Reported results indicate that fractal models provide an adequate framework for medical image processing; consequently high correct classification rates are achieved.

Algorithms↗
PubMed1999

Different flowmotion patterns in healthy controls and patients with Raynaud's phenomenon.

Flowmotion was characterized in healthy controls and 61 Raynaud's phenomenon (RP) patients by spectral analysis of laser-Doppler perfusion monitoring (LDPM) tracings. Healthy subjects flowmotion patterns revealed a main frequency of 3 cycles per min (cpm) with another low frequency and heart rate synchronous components. A first group of RP patients presented a low frequency and heart rate frequency component but no significant difference in blood flow. The second group presented the predominating heart rate related frequency with low microvascular perfusion. The third group presented a flowmotion pattern with overlapping of heart rate and low frequency components. Patients with primary and secondary RP show specific changes in flowmotion, probably related to increased sympathetic nervous activity or vessel wall alterations causing disappearance of arteriolar tone and impairment of microvascular perfusion. The group of patients with overlapping frequency components presents an intermediate flowmotion pattern indicating a different grade of alterations in microvasculature.

Adolescent↗
PubMed1999

[Neural network based detection of pulmonary nodules on chest radiographs].

PURPOSE: We investigated the capabilities of an artificial neural network-based Computer-Aided Diagnosis (CAD) system in improving early detection of pulmonary nodules on chest radiographs. MATERIAL AND METHODS: We used a data-set of 145 digitized chest films. Two different radiologists read the radiographs to detect the sites of possible nodules. The system uses two neural networks trained on a training-set of 100 radiographs selected from the data-set. The first network is used to focus attention on the sites of potential nodules while the second calculates the likeliness of nodule presence in ROIs. The clinical test was performed on 45 more radiographs from the training-set, but different from those in the data-set, which were positive for both benign and malignant nodules. These latter plain films showed 65 nodular lesions which differed by shape and acquisition technique. RESULTS: Sensitivity was 89% in all radiographs while specificity, evaluated by ROI, and accuracy, were 98%. CONCLUSIONS: There are potential limitations in nodule detection on plain radiographs. Some of them are operator-dependent, such as nonsystematic investigation, lesion underestimation, and poor reading, and some are technique-dependent, such as X-ray beam/tube, low voltage, patient positioning, focus-film distance and development process. CADs may contribute to improving detection of pulmonary nodules because the false-negative rate is decreased and sensitivity consequently increased. The high sensitivity and specificity rates of neural networks encourage further trials on wider data-sets to help the radiologist in the early detection of pulmonary nodules.

Humans↗
PubMed1998

Capillary density and leukocyte adhesion in hamsters with hereditary cardiomyopathy.

The aim of this study was to characterize microvascular networks in cheek pouch of cardiomyopathic Syrian hamster (CM) (Bio 14.6), which is an interesting model of idiopathic cardiomyopathy and congestive heart failure. Microcirculation was visualized by fluorescence microscopy. Diameter and length of arterioles, classified according to centrifugal ordering scheme, were measured. A computational method was arranged to determine the density of arterioles and capillaries (total vessel length per unit area, cm-1), fractal dimension of capillaries, and the associated Voronoi tesselation. Furthermore, leukocyte adhesion to venules and arteriolar reactivity to drugs were studied. Increase in the number of terminal arterioles and capillary rarefication characterized CM microvasculature compared with that of age-matched controls (58 +/- 7 versus 25 +/- 5 cm-1, and 128 +/- 15 versus 240 +/- 10 cm-1, respectively). Fractal dimension of capillaries was reduced in CM compared with controls (1. 40 +/- 0.10 versus 1.85 +/- 0.09) and associated with increased avascular spaces, as shown by Voronoi tesselation results. Leukocyte adhesion to venules increased significantly in CM. In CM responsiveness of arterioles to nitric oxide inhibition and propranolol was slighter but more marked to norepinephrine and angiotensin II compared with that of control hamsters. In conclusion, the different geometry, increased leukocyte adhesion, and altered arterial responsiveness may contribute to flow disturbances in the microcirculation of CM hamsters.

Animals↗
PubMed1997

Tissue characterization from X-ray images.

The study of the fine-scale structure of biological tissues is crucial for diagnosing a wide number of different diseases. In X-ray images, fine structures usually induce a correlation among image gray levels and are commonly perceived as textures. In this paper, we report on a Computer Vision approach to the characterization of biological tissues as imaged by standard X-ray techniques. In particular, using features derived from co-occurrence matrices, we have assessed spatial gray-level dependence of bone tissue and lung parenchyma images. A hybrid neural network was adopted to distinguish pathological tissues from normal ones and to classify different pathologies.

Bone Diseases↗
PubMed1995

Automatic analysis of hand radiographs for the assessment of skeletal age: a subsymbolic approach.

The assessment of skeletal maturity is crucial for the analysis of growth disorders and plays an important role in paediatrics. For this reason, several methods have been developed for estimating skeletal maturity. Among them, the Tanner and Whitehouse method (TW2), which is based on the analysis of hand radiographs, is usually considered the most accurate and reliable. Nevertheless, TW2 is applied only in a small fraction of cases, due to its complexity and long examination times. Thus, the development of automated systems which reliably implement this method is highly desirable. However, major difficulties have been found in the development of computer-based systems for the assessment of skeletal maturity. In particular the extraction of the bones of interest has proved to be extremely challenging. In this paper, we propose a system architecture for the implementation of the TW2 method, which is based on artificial neural networks. For each bone considered, the maturation stage is determined by means of a two-step process which first locates the position of the bone in the radiograph and then analyzes the bone shape. Experimental results obtained with our implementation of the carpal version of TW2 are in good agreement with those provided by trained observers.

Adolescent↗
PubMed1995

Synthesis and analytical profile of the new potent antibronchospastic agent 7-[(2,2-dimethyl)propyl]-1-methyl xanthine.

7-[(2,2-Dimethyl)propyl]-1-methyl xanthine (CAS 155006-67-0, MX2/120) is a new potent antibronchospastic agent with negligible side effects. The synthesis involves the alkylation of 3-benzyl-1-methyl xanthine with neopentyl bromide followed by removal of the benzyl protecting group. Main physico-chemical properties were determined using NMR, MS, IR, UV spectra and X-ray crystal structure. A quantitative determination of substances related to MX2/120 and of residual solvents by means of HPLC and GC, respectively, is described. MX2/120 is safely stored at room temperature for a long time.

Bronchodilator Agents↗
PubMed1993

Neural network segmentation of magnetic resonance spin echo images of the brain.

This paper describes a neural network system to segment magnetic resonance (MR) spin echo images of the brain. Our approach relies on the analysis of MR signal decay and on anatomical knowledge; the system processes two early echoes of a standard multislice sequence. Three main subsystems can be distinguished. The first implements a model of MR signal decay; it synthesizes a four-echo multiecho sequence, in order to add images characterized by long echo-times to the input sequence. The second subsystem exploits a priori anatomical knowledge by producing an image, in which pixels belonging to brain parenchyma are highlighted. Such anatomical information allows the following submodule to distinguish biologically different tissues with similar water content, and hence similar appearance, which might produce misclassifications. The grey levels of the reconstructed sequence and the output of the second module are processed by the third subsystem, which performs the segmentation of the sequence. Each pixel is assigned to one of five different tissue classes that can be revealed with brain MR spin echo imaging. With a suitable encoding, a five-level segmented image can then be produced. The system is based on feed-forward networks trained with the back-propagation algorithm; experiments to assess its performance have been carried out on both simulated and clinical images.

Brain↗
PubMed1992

A neural network architecture for understanding discrete three-dimensional scenes in medical imaging.

Magnetic resonance and computed tomography produce sets of tomograms which are termed discrete 3D scenes. Usually, discrete 3D scenes are analyzed in two dimensions by observing each tomogram on a screen so that the three-dimensional information contained in the scene can be recovered only partially and qualitatively. The three-dimensional reconstruction of the shape of biological structures from discrete 3D scenes would allow a complete and quantitative recovery of the available information, but this task has proved hard for conventional processing techniques. In this paper we present a system architecture based on neural networks for the fully automated segmentation and recognition of structures of interest in discrete 3D scenes. The system includes a retina and two main processing modules, an Attention-Focuser System and a Region-Finder System, which have been implemented by using feed-forward nets trained with the back-propagation algorithm. This architecture has been tested on computer-simulated structures and has been applied to the reconstruction of the spinal cord and the brain from sets of tomograms.

Humans↗
PubMed1992

Artificial vision approach to the understanding of heart motion.

To overcome the major drawbacks of conventional descriptive methods, we have developed a computer vision approach to aid understanding of heart motion from a series of sequential X-ray images. The computation is addressed of local descriptors of the heart pumping function from ventricular contours. Physical constraints are exploited such as spatial smoothness of the displacement field and shape correspondence between ventricular boundaries during the beat. A computational method is proposed for the estimation of the displacement field of the left ventricular boundary. Moreover, the spatial arrangement of the estimated motion field is rendered explicit so that it may be utilized in the medical clinic (or for high-level symbolic processing). This is achieved using a grouping criterion which allows the clustering of contiguous points of the left ventricular outline into curve segments which have homogeneous motion properties.

Algorithms↗
PubMed1991

Three-dimensional knowledge driven reconstruction of coronary trees.

A knowledge-driven approach to the three-dimensional reconstruction of coronary artery trees by means of two X-ray projections is proposed. The spatial reconstruction of the tree skeleton is discussed. A binary tree model of the arterial structure and its projections is employed. Consequently, the reconstruction of the three-dimensional tree skeleton is achieved by (a) matching the skeletons of corresponding pairs of vascular segments in the two views and (b) back-projecting the coupled skeleton projections. From a geometrical point of view, the matching problem is, in general, ill-conditioned. For this reason, additional information sources were used. Thus, the matching phase is accomplished by using both the imaging geometry information, as well as anatomical and topological knowledge, about the coronary arteries coded in a rule base. As far as the back-projection phase is concerned, an algorithm was developed based on: (1) the imaging geometry, (2) the bounding of the back-projection error and (3) a contiguity criterion.

Algorithms↗
PubMed1991

Knowledge-based system for the diagnosis and treatment of hypertension.

A knowledge-based system to assist the physician in the diagnosis and treatment of hypertension has been developed as the result of cooperation between the Department of Electronic Engineering of the University of Florence and the Interuniversity Centre of Clinical Chronobiology. The system input consists of the data recorded over a 24 h (or longer) period by monitoring (automatically or through self-measurements) the blood pressure of the subject undergoing the system analysis, and the associated anamnestic data. The process results in a report that states from which kind of hypertensive syndrome, if any, the subject is suffering and which anti-hypertensive therapy appears to be most suitable. The system consists of three modules: the first diagnoses hypertension by applying cluster analysis to a set of parameters derived from the principal components of the time series resulting from the subject's blood pressure monitoring; the other two classify hypertension and offer advice about the most advisable treatment, respectively, by using high-level data representation and processing. The knowledge embedded in the system is internally represented by means of frames and rules. This paper describes the structure of the system, illustrates the techniques that have been used for its development and discusses the results of its application.

Artificial Intelligence↗
PubMed1991

Hypoxia- or hyperoxia-induced changes in arteriolar vasomotion in skeletal muscle microcirculation.

Arteriolar vasomotion was characterized in the skin muscle of the unanesthetized hamster skinfold window preparation and related to the specific arterioles that give rise to the different types of activity. The arterioles were classified according to the Strahler method: order 0 was assigned to capillaries and order 4 to the largest arterioles. The arterioles showed vasomotion with a specific range of frequencies that varied according to the vessel order; the highest fundamental frequency (9.1 +/- 3.9 cycles/min) was detected in the smallest order 1 arterioles and the lowest frequency (2.1 +/- 0.9 cycles/min) in order 4 vessels. Hypoxia (8, 11, and 15% O2 gas mixture inspiration) increased the frequency of vasomotion, decreased mean and effective diameters, and reduced capillary blood flow. The effects were more pronounced with an 8 and 11% O2 gas mixture. Hypoxia caused high-frequency vasomotion to shift from order 1 and 2 arterioles to the beginning of order 3 arterioles, which in this condition dominated the daughter vessels and generated the prominent activity (24 +/- 4 cycles/min, 11% O2 gas mixture). Hypertoxia (100% O2) induced differentiated arteriolar responses. The smallest vessels showed prolonged constriction, decreased mean and effective diameters, and reduced frequency of vasomotion. Capillary blood flow was restricted. Order 3 vessels did not constrict or dilate.

Animals↗
PubMed1990

Superposition of arteriolar vasomotion waves and regulation of blood flow in skeletal muscle microcirculation.

In skin muscle microcirculation of Syrian hamsters, rhythmic diameter changes were studied along the arteriolar network, under normoxic conditions, at rest. A teflon coated-aluminum chamber was implanted in the dorsum skin of animals. The microcirculation was investigated using intravital microscopy technique. Vessel diameters were determined by a computer-assisted method. Power spectrum analysis of vasomotion recordings was carried out with Fast Fourier Transform and Autoregressive modelling. To determine vasomotion waveform spreading, cross-spectral data (amplitude and phase) were computed, using the modified periodogram method (FFT). The arterioles were classified according to Strahler's method. Order 1 vessels (diameter: 7.50 +/- 1.16 microns) showed the highest frequency, 4-15 cycles per min, and percentage amplitude in the range 60-100%. Order 2 and 3 arterioles had intermediate frequencies, and amplitude in the range 50-100%, and 15-50%, respectively. The largest order 4 vessels (diameter: 28.97 +/- 9.55 microns) had the lowest frequency, 0.3-3 cpm, and amplitude in the range 5-20%. In most networks, cross-correlation analysis revealed two groups of frequency components. Low frequency group was propagated from order 4 and 3 vessels downstream. High frequency components were transmitted upstream from order 1 and 2 arterioles. Therefore, a complex superposition of waveforms resulted from the activity of discrete points along the microvasculature. In conclusion, rhythmic diameter changes of arterioles in skeletal muscle microcirculation regulate blood flow distribution in capillary units and control tissue oxygenation.

Animals↗
PubMed1988

Functional microangiopathy in alloxan-treated Syrian hamsters.

Intraperitoneally injected alloxan determined long term hyperglycemia in a group of Syrian hamsters (35 hyperglycemic hamsters); transitory hyperglycemia, with recovery of normal blood glucose concentration but impairment of glucose tolerance test, was observed in a second group of alloxan-treated animals (70 normoglycemic hamsters). Microvascular permeability by fluorescent microscopy technique, capillary basement membrane thickening and pancreatic islet B, A, and D cell degranulation by computer-assisted microdensitometry were studied in Syrian hamsters at different intervals (30, 40, 60, 90, and 120 days) after intraperitoneal alloxan administration. Hyperglycemic groups showed increased permeability of venous microvasculature to high molecular weight dextran in 50%, 71.4%, and 100% of animals studied at 30, 40, and 60, 90, 120 days from treatment, respectively; indeed, they revealed pancreatic islet B cell degranulation and no capillary basement membrane thickening. Normoglycemic groups presented increased venular leakage in 28.5%, 42.8%, 71.4%, and 100% of animals investigated at 40, 60, 90, and 120 days after treatment, respectively; moreover, they showed moderate pancreatic islet B cell degranulation and no capillary basement membrane thickening. In conclusion, more severe microvascular alterations seemed to be related to more severe impairment of glucose metabolism and to longer duration of diabetes; even in normoglycemic hamsters with pathological glucose tolerance test, enhanced permeability developed.

Animals↗
PubMedDate not supplied

A computational approach to medical imaging.

Notwithstanding the progress in medical imaging by means of computer-based techniques, several problems still remain unsolved in this field. In particular, a unified approach for the treatment of biological complexity and variability is lacking. Moreover, perceptive and cognitive aspects of medical vision play an important role in a computational approach to medical imaging and must be carefully considered. The recent developments of Computer Vision and Artificial Intelligence suggest that such a computational approach is feasible. As a consequence, symbolic representations of the clinical information contained in the images as well as adequate processing techniques are necessary. In this way the treatment of uncertainty and the qualitative analysis are made possible. Moreover, due to the intrinsic homogeneity of symbolic representations, the comparison of different image sources, signals and clinical data is attainable. In the paper, the basic principles of Computer Vision are summarized and the need of a specific computational theory for medical vision is emphasized. Afterwards, the main characteristics of integrated systems for computational imaging in medicine, are described. Some examples relative to the imaging of the cardiovascular system are also given. Although the development of artificial vision systems in biomedicine is still an area of research, very promising perspectives are opened by a computational approach.

Artificial Intelligence↗
PubMedDate not supplied

Metabolism of isbufylline in humans. Isolation, identification, and synthesis of plasma and urine metabolites.

Isbufylline metabolism after oral administration to humans was studied. The main metabolites detected by the HPLC method, in plasma, were 1-methyl-7-(2-hydroxy-2-methyl-propyl) xanthine (I), 1,3-dimethyl-7-(2-hydroxy-2-methyl-propyl) xanthine (II), and 1-methyl-7-(2-methyl-propyl) xanthine (III). The main metabolites detected in urine were 1-methyl-7-(2-hydroxy-2-methyl-propyl) xanthine (I), 1,3-dimethyl-7-(2-carboxy-propyl) xanthine (IV), and 1,3-dimethyl-7-(2-hydroxymethyl-propyl) xanthine glucuronic acid (V)-Gluc. They were isolated by HPLC, identified by GC/MS, HPLC/MS, or HPLC/MS/MS, and finally synthesized. Recovery of these metabolites, along with the absence of unmetabolized isbufylline in the urine, indicated biotransformation and renal excretion as the main routes of isbufylline elimination in humans. HPLC quantitation of the characterized urine metabolites revealed that 49% of the drug was eliminated as (I), 9% as (V)-Gluc, and 5% as (IV).

1-Methyl-3-isobutylxanthine↗