Discriminable and Stable Feature Selection for Computer-aided Diagnosis from Sonographic Images - PhD Thesis Proposal

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F05%3A00109899" target="_blank" >RIV/68407700:21230/05:00109899 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Discriminable and Stable Feature Selection for Computer-aided Diagnosis from Sonographic Images - PhD Thesis Proposal

Popis výsledku v původním jazyce

This paper summarises state-of-the-art in feature selection and classification for medical purposes. The main focus is put on sonographic imaging, especially images of the thyroid gland. State-of-the-art covers related works dealing with feature selection and classification (i) in general, (ii) for medical purposes, and (iii) for thyroid gland diseases. It also summarizes works that deal with the task of different scanners and digitizer setting, which may lead to different classification results. The second part of this paper describes our methods and experiences with feature selection and classification applied on sonographic images of thyroid gland. It deals with generating features from sonographic textural images and reproducibility under differentsonograph settings. The last part involves tentative plan for future work to conclude PhD thesis.

Název v anglickém jazyce

Discriminable and Stable Feature Selection for Computer-aided Diagnosis from Sonographic Images - PhD Thesis Proposal

Popis výsledku anglicky

This paper summarises state-of-the-art in feature selection and classification for medical purposes. The main focus is put on sonographic imaging, especially images of the thyroid gland. State-of-the-art covers related works dealing with feature selection and classification (i) in general, (ii) for medical purposes, and (iii) for thyroid gland diseases. It also summarizes works that deal with the task of different scanners and digitizer setting, which may lead to different classification results. The second part of this paper describes our methods and experiences with feature selection and classification applied on sonographic images of thyroid gland. It deals with generating features from sonographic textural images and reproducibility under differentsonograph settings. The last part involves tentative plan for future work to conclude PhD thesis.

Druh

O - Ostatní výsledky

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2005

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů