Koneoppiminen radiologiassa
Abstract
Koneoppiminen on kehittynyt viime aikoina nopeaa vauhtia ja sitä on sovellettu monilla eri aloilla. Tässä kirjallisuuskatsauksessa käsitellään koneoppimisen soveltamista radiologian kuvantamisessa ja siihen liittyviä haasteita. Tutkielmassa käytiin läpi kolmea
sovelluskohdetta kuvantamisessa sekä havaittiin koneoppimiseen liittyviä haasteita radiologiassa. Haasteille kuitenkin löytyi ehdotettuja ratkaisuja.
Machine learning has developed rapidly in recent times and has been applied in a wide range of fields. This literature review discusses the application of machine learning in radiology imaging and the challenges involved. The thesis reviewed three applications in imaging and identified challenges related to machine learning in radiology. However, proposed solutions to these challenges were found.
Machine learning has developed rapidly in recent times and has been applied in a wide range of fields. This literature review discusses the application of machine learning in radiology imaging and the challenges involved. The thesis reviewed three applications in imaging and identified challenges related to machine learning in radiology. However, proposed solutions to these challenges were found.
Main Author
Format
Theses
Bachelor thesis
Published
2024
Subjects
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-202403112327Use this for linking
Language
Finnish