Third International Congress of Histochemistry and Cytochemistry

1968

The tissue distribution of enzymatic activities in intestinal metaplasia stomachs exhibiting chronic gastritis was compared histochemically with that of the small intestine in man.

P621 Efficacy and safety of golimumab in ulcerative colitis. Preliminary data from a multicenter Italian study

2017

A massive lesion detection algorithm in mammography

2004

A new algorithm for massive lesion detection in mammography is presented. The algorithm consists in three main steps : 1) reduction of the dimension of the image to be processed through the identifi cation of regions of interest (rois) as candidates for massive lesions ; 2) characterization of the roi by means of suitable feature extraction ; 3) pattern classifi cation through supervised neural networks. Suspect regions are detected by searching for local maxima of the pixel grey level intensity. A ring of increasing radius, centered on a maximum, is considered until the mean intensity in the ring decreases to a defi ned fraction of the maximum. The rois thus obtained are described by avera…

A completely automated CAD system for mass detection in a large mammographic database

2006

Mass localization plays a crucial role in computer-aided detection (CAD) systems for the classification of suspicious regions in mammograms. In this article we present a completely automated classification system for the detection of masses in digitized mammographic images. The tool system we discuss consists in three processing levels: (a) Image segmentation for the localization of regions of interest (ROIs). This step relies on an iterative dynamical threshold algorithm able to select iso-intensity closed contours around gray level maxima of the mammogram. (b) ROI characterization by means of textural features computed from the gray tone spatial dependence matrix (GTSDM), containing secon…

Detection and classification of microcalcifications clusters in digitized mammograms

2005

In the present paper we discuss a new approach for the detection of microcalcification clusters, based on neural networks and developed as part of the MAGIC-5 project, an INFN-funded program which aims at the development and implementation of CAD algorithms in a GRID-based distributed environment. The proposed approach has as its roots the desire to maximize the rejection of background during the analytical pre-processing stage, in order to train and test the neural network with as clean as possible a sample and therefore maximize its performance. The algorithm is composed of three modules: the image pre-processing, the feature extraction component and the Backpropagation Neural Network mod…

Mammogram Segmentation by Contour Searching and Mass Lesions Classification with Neural Network

2006

The mammography is the most effective procedure for an early diagnosis of the breast cancer. In this paper, an algorithm for detecting masses in mammographic images will be presented. The database consists of 3762 digital images acquired in several hospitals belonging to the MAGIC-5 collaboration (Medical Applications on a Grid Infrastructure Connection). A reduction of the whole image's area under investigation is achieved through a segmentation process, by means of a ROI Hunter algorithm, without loss of meaningful information. In the following classification step, feature extraction plays a fundamental role: some features give geometrical information, other ones provide shape parameters.…

GPCALMA: A Grid-based tool for mammographic screening

2005

The next generation of High Energy Physics (HEP) experiments requires a GRID approach to a distributed computing system and the associated data management: the key concept is the Virtual Organisation (VO), a group of distributed users with a common goal and the will to share their resources. A similar approach is being applied to a group of Hospitals which joined the GPCALMA project (Grid Platform for Computer Assisted Library for MAmmography), which will allow common screening programs for early diagnosis of breast and, in the future, lung cancer. HEP techniques come into play in writing the application code, which makes use of neural networks for the image analysis and proved to be useful…

Clinical and economic impact of infliximab one-hour infusion protocol in patients with inflammatory bowel diseases: A multicenter study

2017

AIM To assess the impact of short infliximab (IFX) infusion on hospital resource utilization and costs. METHODS All inflammatory bowel diseases (IBD) patients who received IFX 1 h infusion from March 2007 to September 2014 in eight centers from Southern Italy were included in the analysis. Demographic, clinical and infusion related data were collected. The potential benefits related to the short infusion protocol were assessed both in terms of time saving and increased infusion unit capacity. In addition, indirect patient-related cost savings were evaluated. RESULTS One hundred and twenty-five patients were recruited (64 with ulcerative colitis and 61 with Crohn’s disease). Median duration …

The MAGIC-5 Project: Medical Applications on a Grid Infrastructure Connection

2004

Mammogram segmentation by contour searching and massive lesion classification with neural network

2004

The mammography is the most effective procedure for an early diagnosis of the breast cancer. In this paper, an algorithm for detecting massive lesions in mammographic images will be presented. The database consists of 3762 digital images acquired in several hospitals belonging to the MAGIC-5 collaboration. A reduction of the surface under investigation is achieved, without loss of meaningful information, through segmentation of the whole image, by means of a ROI Hunter algorithm. In the following classification step, feature extraction plays a fundamental role: some features give geometrical information, other ones provide shape parameters. Once the features are computed for each ROI, they …