Principles and clinical applications of autocontouring software
Collana
Livello
Testi per professional
Dati
pp. 20,      1a edizione  2014   (Codice editore 2000.1409)

Tipologia: E-book (PDF) per PC, Mac, Tablet
Prezzo: € ,00
Possibilità di stampa:  No
Possibilità di copia:  No
Possibilità di annotazione:  Si
Formato: PDF con DRM per Digital Editions
Tipologia: E-book (ePub) per PC, Mac, Tablet
Prezzo: € ,00
Formato: Epub con DRM per Digital Editions
Codice ISBN: 9788891703682
Informazioni sugli e-book



In breve
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Presentazione del volume



The recently released autocontouring and advanced imaging software are rapidly gaining growing attention in the contemporary scientific landscape.
Their aim is to lower the contouring time burden, allowing in the meanwhile a more accurate adherence to the existing guidelines and strongly reducing the interobserver variability which still represents a major source of error in Radiotherapy.
But besides these promising benefits, the user must be aware that these software still present technical and ontological limits that could decrease their clinical reliability.
Aim of this ebook is to present the existing state of art, to support those who intend to report their experiences with autocontouring software and to describe the principal aspects and variables that must be considered and analyzed when setting up a research study directed to efficaciously evaluate these software.
The different aspects of this fascinating topic will be highlighted in specific units of knowledge, where the text is enriched by figures, tables and fully interactive widgets that assure a faster and easier learning.

Luca Boldrini is a medical doctor of the UCSC Radiation Oncology Department, in Rome. The use of multimodal imaging modalities for radiation therapy planning purposes and the clinical-physical validation of the autocontouring and advanced imaging software are his main areas of interest.
Andrea Damiani is an expert in Mathematical modeling and works with UCSC on geometric models for contouring evaluation and Automated Learning from data and images. He published educational books and interactive applications in the fields of Mathematics and Physics.
Vincenzo Valentini is Professor and Chair of the UCSC Radiation Oncology Department and Knowledge Based Oncology Labs, in Rome. His main topics of scientific investigation are the multidisciplinary management of cancer, knowledge based oncology, radiomics and e-learning development in Medicine.

Indice
Introduction
The definition of the ontology
Defining the benchmark
Who, what and when of similarity indices
Describing the benefit
Conclusions. Recommendations for reporting: advice and suggestions





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