Applicability of Radiomics for Differentiation of Pancreatic Adenocarcinoma from Healthy Tissue of Pancreas by Using Magnetic Resonance Imaging and Machine Learning
The machine learning approach using radiomics features extracted from T2W-FS and ADC achieved a relatively high sensitivity in the differentiation of pancreatic adenocarcinoma from healthy pancreatic tissue, which could be especially applicable for screening purposes.
Authors
- Milica Badža Atanasijević (ORCID: https://orcid.org/0000-0002-5856-2626)
- Aleksandra Djurić-Stefanović (ORCID: https://orcid.org/0000-0002-5796-835X)
- Dušan Šaponjski (ORCID: https://orcid.org/0000-0002-6640-234X)
- Dragan Mašulović (ORCID: https://orcid.org/0000-0002-5016-1908)
- Jelena Djokić Kovač
- Katarina Stošić (ORCID: https://orcid.org/0000-0002-2447-1574)
- Dimitrije Šarac (ORCID: https://orcid.org/0009-0009-5799-656X)
- Veljko Papić (ORCID: https://orcid.org/0000-0002-5483-7530)
- Dejan Radenković (ORCID: https://orcid.org/0000-0002-1029-3762)
- Stefan Milošević (ORCID: https://orcid.org/0000-0001-9855-1633)
- Milica Mitrović-Jovanović (ORCID: https://orcid.org/0000-0002-7525-7615)
- Aleksandra Janković (ORCID: https://orcid.org/0000-0002-8239-1724)
- Ljubica Lazić
Institutions
- University of Belgrade (RS)
- Univerzitetski Klinički Centar Srbije (RS)
Publication Details
- Journal
- Cancers
- Published
- 2025-03-27
- DOI
- https://doi.org/10.3390/cancers17071119
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36