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pro vyhledávání: '"Nieminen, Miika T."'
Knee Osteoarthritis (KOA) is a highly prevalent chronic musculoskeletal condition with no currently available treatment. The manifestation of KOA is heterogeneous and prediction of its progression is challenging. Current literature suggests that the
Externí odkaz:
http://arxiv.org/abs/2307.00873
Multi-energy computed tomography (CT) with photon counting detectors (PCDs) enables spectral imaging as PCDs can assign the incoming photons to specific energy channels. However, PCDs with many spectral channels drastically increase the computational
Externí odkaz:
http://arxiv.org/abs/2211.01159
Autor:
Isosalo, Antti, Inkinen, Satu I., Prostredná, Lucia, Heino, Helinä, Ipatti, Pieta S., Reponen, Jarmo, Nieminen, Miika T.
Publikováno v:
In Computers in Biology and Medicine December 2024 183
Accurate prediction of knee osteoarthritis (KOA) progression from structural MRI has a potential to enhance disease understanding and support clinical trials. Prior art focused on manually designed imaging biomarkers, which may not fully exploit all
Externí odkaz:
http://arxiv.org/abs/2201.10849
Objective is to assess the ability of texture features for detecting radiographic patellofemoral osteoarthritis (PFOA) from knee lateral view radiographs. We used lateral view knee radiographs from MOST public use datasets (n = 5507 knees). Patellar
Externí odkaz:
http://arxiv.org/abs/2106.01700
Objective: To assess the ability of imaging-based deep learning to predict radiographic patellofemoral osteoarthritis (PFOA) from knee lateral view radiographs. Design: Knee lateral view radiographs were extracted from The Multicenter Osteoarthritis
Externí odkaz:
http://arxiv.org/abs/2101.04350
Publikováno v:
In Physica Medica January 2024 117
Knee osteoarthritis (OA) is very common progressive and degenerative musculoskeletal disease worldwide creates a heavy burden on patients with reduced quality of life and also on society due to financial impact. Therefore, any attempt to reduce the b
Externí odkaz:
http://arxiv.org/abs/2005.11715
Akademický článek
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Autor:
Bayramoglu, Neslihan, Tiulpin, Aleksei, Hirvasniemi, Jukka, Nieminen, Miika T., Saarakkala, Simo
The purposes of this study were to investigate: 1) the effect of placement of region-of-interest (ROI) for texture analysis of subchondral bone in knee radiographs, and 2) the ability of several texture descriptors to distinguish between the knees wi
Externí odkaz:
http://arxiv.org/abs/1908.07736