"Äyrämö, Sami" - Selaus tekijän mukaan TUNICRIS-julkaisut
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An Automatic Method for Assessing Spiking of Tibial Tubercles Associated with Knee Osteoarthritis
Patron, Anri; Annala, Leevi; Lainiala, Olli; Paloneva, Juha; Äyrämö, Sami (10 / 2022)
article<p>Efficient and scalable early diagnostic methods for knee osteoarthritis are desired due to the disease’s prevalence. The current automatic methods for detecting osteoarthritis using plain radiographs struggle to ... -
Change of Direction Biomechanics in a 180-Degree Pivot Turn and the Risk for Noncontact Knee Injuries in Youth Basketball and Floorball Players
Leppänen, Mari; Parkkari, Jari; Vasankari, Tommi; Äyrämö, Sami; Kulmala, Juha Pekka; Krosshaug, Tron; Kannus, Pekka; Pasanen, Kati (2021)
article<p>Background: Studies investigating biomechanical risk factors for knee injuries in sport-specific tasks are needed. Purpose: To investigate the association between change of direction (COD) biomechanics in a ... -
Domain-specific transfer learning in the automated scoring of tumor-stroma ratio from histopathological images of colorectal cancer
Petäinen, Liisa; Väyrynen, Juha P.; Ruusuvuori, Pekka; Pölönen, Ilkka; Äyrämö, Sami; Kuopio, Teijo (05 / 2023)
article<p>Tumor-stroma ratio (TSR) is a prognostic factor for many types of solid tumors. In this study, we propose a method for automated estimation of TSR from histopathological images of colorectal cancer. The method is ... -
H&E Multi-Laboratory Staining Variance Exploration with Machine Learning
Prezja, Fabi; Pölönen, Ilkka; Äyrämö, Sami; Ruusuvuori, Pekka; Kuopio, Teijo (08 / 2022)
article<p>In diagnostic histopathology, hematoxylin and eosin (H&E) staining is a critical process that highlights salient histological features. Staining results vary between laboratories regardless of the histopathological ... -
Multilabel segmentation of cancer cell culture on vascular structures with deep neural networks
Rahkonen, Samuli; Koskinen, Emilia; Pölönen, Ilkka; Heinonen, Tuula; Ylikomi, Timo; Äyrämö, Sami; Eskelinen, Matti A. (2020)
article<p>New increasingly complex in vitro cancer cell models are being developed. These new models seem to represent the cell behavior in vivo more accurately and have better physiological relevance than prior models. An ...