Biomedical subjects

O Salvetti

Publications and source records attributed to O Salvetti.

7 recordsLinked to original sources

PubMed1998

Volumetric analysis of CT orbital images.

The determination of the volume of eye muscles is a problem of considerable interest in Graves' ophtalmopathy both with respect to the diagnostic quantisation of the disease and to the measured assessment of the effectiveness of pharmacological treatment. The aim of this research is to design and test an advanced method for processing computerised tomography (CT) orbital images in order to obtain a three-dimensional reconstruction of infra-orbital muscle structures and to analyse them from a morphometric viewpoint. CT images of subjects suffering from Graves' disease were acquired before and after pharmacological treatment with immunosuppressors. They were then processed along with CT images of an anatomical phantom of known volume and fusiform morphology in order to assess the reliability of the procedure and to calculate the effect of the different modalities of acquisition and processing of CT images on the error in volume calculation.

Graves Disease↗

PubMed1997

Deformation analysis of brain regions.

The analysis of 2D and 3D deformations applied to structures having non regular geometry is presented. Deformations are studied in order to understand complex dynamic problems coded into image sequences. In particular, methods have been developed suitable to control the reconstruction and the spatial deformation of cerebral structures, in their different aspects of morphometry, isometry and densitometry. Finally, a simulation process of brain deformation caused by a neoplasia in a real relevant clinical case has been performed.

Brain↗

PubMed1996

An intelligent system for the diagnosis of complex images.

An intelligent system suitable to perform a computer aided diagnosis of complex images should have a knowledge base containing all information related both to the images to be interpreted and to their symbolic description. In this paper, a system able to classify unknown medical digital images into four classes is proposed (searched pathology recognized, searched pathology absent, different pathology from the searched one recognized, unknown pathology). A main component of this system is a knowledge base that, startling from information deduced from sample images, can be processed to create synthetic reference models that, in turn, permit the interpretation of real scenes. The system has been tested on digitized plain film of the thorax, in order to perform a computer-aided diagnosis of pneumothorax cases.

Artificial Intelligence↗

PubMed1996

[Quantitative evaluation of the dynamics of the coronary wall in man: description of a new method based on tridimensional time-dependent reconstruction of intravascular ultrasonographic images].

BACKGROUND: Intravascular ultrasound imaging provides information on vascular lumen and arterial wall structure and it has potential application in arterial wall dynamic study. The aim of this study was to develop a computer assisted system for analysing digitised cross sectional ultrasound images of coronaries to easily display and quantify coronary dynamic and its relationship with arterial wall morphology. METHODS AND RESULTS: To extract the anatomical regions of interest from the digitised sonograms, automatic image segmentation and interactive procedures for manual correction were implemented. This step included the recognition of the lumen edge and an analysis of gray level intensity of the wall. Subsequently, a virtual 3D reconstruction of lumen and vessel wall was done in a Cartesian system where the XY plane was parallel to each cross-sectional sonogram, while the Z axis corresponded to the acquisition time. The baricentre of vascular lumen was used as a reference for alignment. We obtained a cylinder-like solid representing the behavior of the arterial cross-sectional sonogram in time, with the possibility to look either at the wall or at the lumen. In this virtual solid it was possible to measure the variation of lumen area and of 16 hemidiameters; in addition, the derivatives of these values, allowing an estimate of the velocity of events, can be obtained. CONCLUSIONS: The described computerised system for the analysis of intravascular ultrasound images could become a very useful tool for 3D representation and quantitative monitoring of coronary compliance and their relationship with segmental arterial wall morphology.

Coronary Vessels↗

PubMed1989

Decrease of diffusion of glycosylated albumin in retinal microcirculation by peptide fraction from bovine factor VIII.

The diffusion of the glycosylated albumin in the retinal vascular system has been studied in male New Zealand rabbits, using fluorangiographic techniques. A first group of animals was treated for 15 days with the peptide fraction from bovine Factor VIII (Vueffe); a second group, used as control group, was treated with physiological solution. At the end of treatment, glycosylated albumin was made fluorescent and then injected into the marginal vein of the rabbit. The direct observation and the photometric measurements performed on the digitized photograms with an image processing system showed a considerable reduction in retinic capillary diffusion of glycosylated albumin in the animals treated with the peptide fraction. The substance used in the study might therefore be of importance in the treatment of systemic disease with retinic vascular damage.

Angiography↗

PubMedDate not supplied

Morphometric analysis of sonographic images by spatial geometric modeling.

A methodology able to derive spatial geometric models from input sequences of sonographic slices is proposed. The developed modeling procedure can be utilized to perform computer-assisted anatomic 3D analysis both on all echo space and selected subregions. The modeling procedure is mainly composed of three sequential phases: a) automatic acquisition and preprocessing of time sequences of 2D echotomograms; b) 3D reconstruction of images and computing of discrete distance maps of selected echoes according to predefined projective laws; and c) generation of a spatial geometric model of the examined object starting from the previously computed maps.

Algorithms↗

PubMedDate not supplied

[The evaluation of a digital system for the automatic analysis of the density of abdominal radiograms].

This paper reports the results of the evaluation of an automatic system developed to analyze radiographic densities. This system, called RADEN, has been implemented at the Institute for Information Processing of the Italian National Research Council in Pisa. Forty-three pairs of abdominal X-ray films were obtained before and after the administration of ionic iodate contrast medium (i.i.c.m.) during urographic examinations. The 86 X-ray films were acquired and digitized using a computer-controlled optoelectronic device with a sampling step ranging 125 microns to 250 microns. The resulting images were arrays of 512 x 512 pixels, each one quantified on a byte (256 gray levels). The computing system included a high-performance personal computer equipped with a video RAM board having built-in facilities for image processing and with an optical disk to archive the images. Automatic and semi-automatic procedures were developed to segment, recognize and classify the images and to characterize three homogeneous regions--i.e., bone, water and air. The output data were compared with the area values of the air densities computed directly on the X-ray films by a radiologist. Furthermore, both data sets were compared with the scores given in a blind study by four observers. The subsequent statistic analysis showed the increase in air density areas after i.i.c.m. administration and the applicability of the implemented system to the automatic examination of abdominal radiographic densities. The results encourage to believe that the proposed approach could be employed as a first step for the development of quite a more complex system oriented to X-ray image understanding and to assisted diagnosis.

Contrast Media↗