An automatic method for assessing spiking of tibial tubercles associated with knee osteoarthritis

Polvinivelrikon kasvavan esiintyvyyden vuoksi tehokkaat varhaiset diagnoosimenetelmät ovat haluttavia. Radiografia on keskeinen osa polvinivelrikon diagnostiikassa. Polvinivelrikon varhainen tunnistaminen on haastavaa, sillä tärkeimpiä polvinivelrikon merkkejä on vaikea havaita röntgenkuvista taudin...

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Main Author: Patron, Anri
Other Authors: Informaatioteknologian tiedekunta, Faculty of Information Technology, Informaatioteknologia, Information Technology, Jyväskylän yliopisto, University of Jyväskylä
Format: Master's thesis
Language:eng
Published: 2022
Subjects:
Online Access: https://jyx.jyu.fi/handle/123456789/84280
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author Patron, Anri
author2 Informaatioteknologian tiedekunta Faculty of Information Technology Informaatioteknologia Information Technology Jyväskylän yliopisto University of Jyväskylä
author_facet Patron, Anri Informaatioteknologian tiedekunta Faculty of Information Technology Informaatioteknologia Information Technology Jyväskylän yliopisto University of Jyväskylä Patron, Anri Informaatioteknologian tiedekunta Faculty of Information Technology Informaatioteknologia Information Technology Jyväskylän yliopisto University of Jyväskylä
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description Polvinivelrikon kasvavan esiintyvyyden vuoksi tehokkaat varhaiset diagnoosimenetelmät ovat haluttavia. Radiografia on keskeinen osa polvinivelrikon diagnostiikassa. Polvinivelrikon varhainen tunnistaminen on haastavaa, sillä tärkeimpiä polvinivelrikon merkkejä on vaikea havaita röntgenkuvista taudin varhaisessa vaiheessa. Koneoppimallien kehittämistä varhaiseen polvinivelrikon tunnistamiseen vaikeuttaa lisäksi saatavilla olevan datan kohinaisuus. Tämän tutkielman tavoitteena oli tarkastella hypoteesia eminentian terävöitymisestä varhaisen polvinivelrikon piirteenä. Tutkielmassa kehitettiin myös neuroverkkopohjainen malli piirteen tunnistamiseen röntgenkuvista. Työn tulokset viittaavat eminentian terävyyden olevan yhteydessä varhaiseen polvinivelrikkoon. Tämän lisäksi piirre voidaan tunnistaa automaattisesti röntgenkuvista. Työn tuloksia voidaan pitää kuitenkin vasta alustavina. Efficient and scalable early diagnostic methods are warranted due to the rising prevalence of knee osteoarthritis. Radiographic imaging is the standard procedure in osteoarthritis diagnosis. However, the circumstances for early diagnosis are problematic since the plain radiographs are insensitive to the established early signs of knee osteoarthritis. Furthermore, developing machine learning tools for radiographic knee osteoarthritis diagnosis is challenging due to noisy ground-truth. The objective of this thesis was to assess a feature called spiking of tibial tubercles, which has been hypothesized as an early sign of knee osteoarthritis. Additionally, we developed a model based on neural networks for identifying the feature in plain radiographs. Our results indicate promise in including tibial spiking as an early feature of knee osteoarthritis, and the feature is identifiable automatically. However, the work in the current thesis is limited and should be validated by future work.
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spellingShingle Patron, Anri An automatic method for assessing spiking of tibial tubercles associated with knee osteoarthritis Tietotekniikka Mathematical Information Technology 602 polvet nivelrikko koneoppiminen neuroverkot radiologia nivelet knees arthrosis machine learning neural networks (information technology) radiology joints (musculoskeletal system)
title An automatic method for assessing spiking of tibial tubercles associated with knee osteoarthritis
title_full An automatic method for assessing spiking of tibial tubercles associated with knee osteoarthritis
title_fullStr An automatic method for assessing spiking of tibial tubercles associated with knee osteoarthritis An automatic method for assessing spiking of tibial tubercles associated with knee osteoarthritis
title_full_unstemmed An automatic method for assessing spiking of tibial tubercles associated with knee osteoarthritis An automatic method for assessing spiking of tibial tubercles associated with knee osteoarthritis
title_short An automatic method for assessing spiking of tibial tubercles associated with knee osteoarthritis
title_sort automatic method for assessing spiking of tibial tubercles associated with knee osteoarthritis
title_txtP An automatic method for assessing spiking of tibial tubercles associated with knee osteoarthritis
topic Tietotekniikka Mathematical Information Technology 602 polvet nivelrikko koneoppiminen neuroverkot radiologia nivelet knees arthrosis machine learning neural networks (information technology) radiology joints (musculoskeletal system)
topic_facet 602 Mathematical Information Technology Tietotekniikka arthrosis joints (musculoskeletal system) knees koneoppiminen machine learning neural networks (information technology) neuroverkot nivelet nivelrikko polvet radiologia radiology
url https://jyx.jyu.fi/handle/123456789/84280 http://www.urn.fi/URN:NBN:fi:jyu-202212125538
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