A machine-learning approach to the automated assessment of joint synovitis activity

Konrad Wojciechowski; Bogdan Smolka; Rafal Cupek; Adam Ziebinski; Karolina Nurzynska; Marek Kulbacki; Jakub Segen; Marcin Fojcik; Pawel Mielnik; Sebastian Hein

doi:10.1007/978-3-319-45246-3_42

A machine-learning approach to the automated assessment of joint synovitis activity

Konrad Wojciechowski
, Bogdan Smolka
, Rafal Cupek
, Adam Ziebinski
, Karolina Nurzynska
, Marek Kulbacki
, Jakub Segen
, Marcin Fojcik
, Pawel Mielnik
, Sebastian Hein

Polish-Japanese Academy of Information Technology
Høgskulen i Sogn og Fjordane
Helse Førde
Institute of Medical Technology and Equipment

Wyniki badań: Wkład do czasopisma › Artykuł z konferencji › recenzja

3 Cytowania z bazy Scopus

Abstrakt

Medical ultrasound imaging is an important tool in diagnosing and monitoring synovitis, which is an inflammation of the synovial membrane that surrounds a joint. Ultrasound images are examined by medical experts to assess the presence and progression of synovitis. Automating image analysis reduces the costs and increases the availability of the ultrasound diagnosis of synovitis and diminishes or eliminates subjective discrepancies. This article describes research that is concerned with the problem of the automatic estimation of the state of the activity of finger joint inflammation using the information that is present in ultrasonography imaging.

Język oryginału	angielski
Strony (od–do)	440-450
Liczba stron	11
Czasopismo	Lecture Notes in Computer Science
Tom	9876 LNCS
Identyfikatory DOI	https://doi.org/10.1007/978-3-319-45246-3_42
Status publikacji	Opublikowano - 2016
Wydarzenie	8th International Conference on Computational Collective Intelligence, ICCCI 2016 - Halkidiki, Grecja Czas trwania: 28 wrz 2016 → 30 wrz 2016

Obszary tematyczne ASJC Scopus

Informatyka teoretyczna
Informatyka ogólna

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10.1007/978-3-319-45246-3_42

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Cytowanie

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title = "A machine-learning approach to the automated assessment of joint synovitis activity",

abstract = "Medical ultrasound imaging is an important tool in diagnosing and monitoring synovitis, which is an inflammation of the synovial membrane that surrounds a joint. Ultrasound images are examined by medical experts to assess the presence and progression of synovitis. Automating image analysis reduces the costs and increases the availability of the ultrasound diagnosis of synovitis and diminishes or eliminates subjective discrepancies. This article describes research that is concerned with the problem of the automatic estimation of the state of the activity of finger joint inflammation using the information that is present in ultrasonography imaging.",

author = "Konrad Wojciechowski and Bogdan Smolka and Rafal Cupek and Adam Ziebinski and Karolina Nurzynska and Marek Kulbacki and Jakub Segen and Marcin Fojcik and Pawel Mielnik and Sebastian Hein",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 8th International Conference on Computational Collective Intelligence, ICCCI 2016 ; Conference date: 28-09-2016 Through 30-09-2016",

year = "2016",

doi = "10.1007/978-3-319-45246-3\_42",

language = "English",

volume = "9876 LNCS",

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journal = "Lecture Notes in Computer Science",

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TY - JOUR

T1 - A machine-learning approach to the automated assessment of joint synovitis activity

AU - Wojciechowski, Konrad

AU - Smolka, Bogdan

AU - Cupek, Rafal

AU - Ziebinski, Adam

AU - Nurzynska, Karolina

AU - Kulbacki, Marek

AU - Segen, Jakub

AU - Fojcik, Marcin

AU - Mielnik, Pawel

AU - Hein, Sebastian

PY - 2016

Y1 - 2016

N2 - Medical ultrasound imaging is an important tool in diagnosing and monitoring synovitis, which is an inflammation of the synovial membrane that surrounds a joint. Ultrasound images are examined by medical experts to assess the presence and progression of synovitis. Automating image analysis reduces the costs and increases the availability of the ultrasound diagnosis of synovitis and diminishes or eliminates subjective discrepancies. This article describes research that is concerned with the problem of the automatic estimation of the state of the activity of finger joint inflammation using the information that is present in ultrasonography imaging.

AB - Medical ultrasound imaging is an important tool in diagnosing and monitoring synovitis, which is an inflammation of the synovial membrane that surrounds a joint. Ultrasound images are examined by medical experts to assess the presence and progression of synovitis. Automating image analysis reduces the costs and increases the availability of the ultrasound diagnosis of synovitis and diminishes or eliminates subjective discrepancies. This article describes research that is concerned with the problem of the automatic estimation of the state of the activity of finger joint inflammation using the information that is present in ultrasonography imaging.

UR - https://www.scopus.com/pages/publications/84990047473

U2 - 10.1007/978-3-319-45246-3_42

DO - 10.1007/978-3-319-45246-3_42

M3 - Conference article

AN - SCOPUS:84990047473

SN - 0302-9743

VL - 9876 LNCS

SP - 440

EP - 450

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

T2 - 8th International Conference on Computational Collective Intelligence, ICCCI 2016

Y2 - 28 September 2016 through 30 September 2016

ER -

A machine-learning approach to the automated assessment of joint synovitis activity

Abstrakt

Obszary tematyczne ASJC Scopus

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