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Radiomics and artificial intelligence analysis of CT data for the identification of prognostic features in multiple myeloma
- Publication Year :
- 2020
-
Abstract
- Multiple Myeloma (MM) is a blood cancer implying bone marrow involvement, renal damages and osteolytic lesions. The skeleton involvement of MM is at the core of the present paper, exploiting radiomics and artificial intelligence to identify image-based biomarkers for MM. Preliminary results show that MM is associated to an extension of the intrabone volume for the whole body and that machine learning can identify CT image features mostly correlating with the disease evolution. This computational approach allows an automatic stratification of MM patients relying of these biomarkers and the formulation of a prognostic procedure for determining the disease follow-up.
- Subjects :
- Quantitative Biology - Tissues and Organs
92C55, 68T10, 68U10
68U10
68T10
Blood cancer
Radiomics
medicine
Tissues and Organs (q-bio.TO)
image segmentation
Multiple myeloma
business.industry
clustering
image features
x-ray ct
92C55
Image segmentation
medicine.disease
medicine.anatomical_structure
Disease evolution
FOS: Biological sciences
Bone marrow
Artificial intelligence
Whole body
business
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....4b8cb10ab2455c151abaaf2e82e172b8