Machine learning applications for multi-scale computed tomography of skeletal tissues

Approved

Classifications

MinEdu publication type
G5 Doctoral dissertation (articles)
Definition
Thesis
Thesis
Article dissertation
Target group
Scientific

Authors of the publication

Number of authors
1
Authors
Rytky, Santeri

Publication channel information

ISBN (print)
978-952-62-3895-1
ISBN (electronic)
978-952-62-3896-8
Title of journal/series
Acta Universitatis Ouluensis. Series D, Medica
ISSN (print)
0355-3221
ISSN (electronic)
1796-2234
ISSN (linking)
0355-3221
Publisher
Oulun yliopisto
Country of publication
Finland
Internationality
No

Detailed publication information

Publication year
2023
Reporting year
2023
Journal/series issue number
1754
Page numbers
152
Language of publication
English

Co-publication information

International co-publication
No
Co-publication with a company
No

Availability

Link to online publication

Classification and additional information

MinEdu field of science classification
217 Medical engineering
Keywords
cone-beam computed tomography; contrast-enhanced micro-computed tomography; histopathological grading; machine learning; osteoarthritis; segmentation; super-resolution; histopatologinen arviointi; kartiokeilatietokonetomografia; koneoppiminen; kontrastitehosteinen mikrotietokonetomografia; nivelrikko; segmentointi; super-resoluutio

Funding information

Funding information in the publication
The Instrumentarium Science Foundation, Finnish Cultural Foundation, European Research Council and Academy of Finland are recognized for financial support.

Source database ID

Other database ID
Finna: jultika.isbn978-952-62-3896-8