Search results for "informatica"

A novel framework for MR image segmentation and quantification by using MedGA

2019

BACKGROUND AND OBJECTIVES: Image segmentation represents one of the most challenging issues in medical image analysis to distinguish among different adjacent tissues in a body part. In this context, appropriate image pre-processing tools can improve the result accuracy achieved by computer-assisted segmentation methods. Taking into consideration images with a bimodal intensity distribution, image binarization can be used to classify the input pictorial data into two classes, given a threshold intensity value. Unfortunately, adaptive thresholding techniques for two-class segmentation work properly only for images characterized by bimodal histograms. We aim at overcoming these limitations and…

Computer-Assisted Approaches for Uterine Fibroid Segmentation in MRgFUS Treatments: Quantitative Evaluation and Clinical Feasibility Analysis

2019

Nowadays, uterine fibroids can be treated using Magnetic Resonance guided Focused Ultrasound Surgery (MRgFUS), which is a non-invasive therapy exploiting thermal ablation. In order to measure the Non-Perfused Volume (NPV) for treatment response assessment, the ablated fibroid areas (i.e., Region of Treatment, ROT) are manually contoured by a radiologist. The current operator-dependent methodology could affect the subsequent follow-up phases, due to the lack of result repeatability. In addition, this fully manual procedure is time-consuming, considerably increasing execution times. These critical issues can be addressed only by means of accurate and efficient automated Pattern Recognition ap…

An Iconic Framework for Learning the Art of Programming

2016

The integration of programming teachings, in all levels of education, highlights the need to acquire the art of programming for each individual student through versatile tools based on specific cognitive methods. Diversified linguistic metaphors have to be adopted by the developing frame, in order to highlight the qualities of each student. Therefore, a framework, oriented to learning the art of programming, must foster polychrome constructs representations, a number of data structures and an intuitive interfaces in order to make easier to understand the evolution of the algorithm that have to be developed. The following contribution will present a theoretical formalization of a framework f…

Deep Metric Learning for Transparent Classification of Covid-19 X-Ray Images

2022

This work proposes an interpretable classifier for automatic Covid-19 classification using chest X-ray images. It is based on a deep learning model, in particular, a triplet network, devoted to finding an effective image embedding. Such embedding is a non-linear projection of the images into a space of reduced dimension, where homogeneity and separation of the classes measured by a predefined metric are improved. A K-Nearest Neighbor classifier is the interpretable model used for the final classification. Results on public datasets show that the proposed methodology can reach comparable results with state of the art in terms of accuracy, with the advantage of providing interpretability to t…

Image segmentation to evaluate islets of langherans

2008

This contribution deals with an unsupervised system to process digital photomicrographs in order to locate and analyze islets of Langherans in human pancreases. The experiment has been conducted on real data and, though we are still going to complete the evaluation of the whole method, we expect to define a set of proper features (e.g. area, perimeter, fractal dimension, shape complexity, texture and entropy) useful for a fast and reliable counting of healthy cells. In particular, this research aims to measure the advisability of a possible implantation in patients affected by type I diabetes mellitus

Dissecting and Reassembling Color Correction Algorithms for Image Stitching

2018

This paper introduces a new compositional framework for classifying color correction methods according to their two main computational units. The framework was used to dissect fifteen among the best color correction algorithms and the computational units so derived, with the addition of four new units specifically designed for this work, were then reassembled in a combinatorial way to originate about one hundred distinct color correction methods, most of which never considered before. The above color correction methods were tested on three different existing datasets, including both real and artificial color transformations, plus a novel dataset of real image pairs categorized according to …

Informatica per le Scienze Motorie

2008

L’informatica umanistica: attualità e prospettive

2010

"Tea for two": the Archive of the Italian Latinity of the Middle Ages meets the CLARIN infrastructure

2020

This paper aims at showing how integrating the Archive of the Italian Latinity of the Middle Ages (ALIM) into the ILC4CLARIN repository can provide mutual benefits. Making ALIM available to a large community of scholars and researchers, on the one side, represents the first step to reduce the lack of resources for Medieval Latin in CLARIN and, on the other side, constitutes an unprecedented contribution to not only linguistic investigations, but also to the studies of the culture and science at the basis of the Western European society. The paper describes the adopted approach aiming to keep intact the structure of the archive and its metadata, which are both accurately mirrored into the IL…

Learned Sorted Table Search and Static Indexes in Small-Space Data Models

2023

Machine-learning techniques, properly combined with data structures, have resulted in Learned Static Indexes, innovative and powerful tools that speed up Binary Searches with the use of additional space with respect to the table being searched into. Such space is devoted to the machine-learning models. Although in their infancy, these are methodologically and practically important, due to the pervasiveness of Sorted Table Search procedures. In modern applications, model space is a key factor, and a major open question concerning this area is to assess to what extent one can enjoy the speeding up of Binary Searches achieved by Learned Indexes while using constant or nearly constant-space mod…