15.00 |
|
Welcome and lntroduction |
SESSION 1 |
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15.10 |
|
Optimization of structural similarity in image analysis and visual quality |
15.25 |
|
How can we make radiomics and deep learning explainable? |
15.40 |
|
Discussion |
15.55 |
|
Feature Engineering versus Feature Learning for Radiomics |
16.10 |
|
Radiomics and rectal cancer: a promising application |
16.25 |
|
Discussion |
SESSION 2 |
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16.40 |
|
Radiomics and hadrontherapy: where we are now? |
16.55 |
|
Radiomics and whole-body MRI |
17.05 |
|
Discussion |
17.20 |
|
Autosegmentation strategies in prostate cancer |
17.30 |
|
Deep Learning in prostate cancer radiomics |
17.40 |
|
Prostate cancer radiomics in the clinics: ready for prime time? |
17.50 |
|
Artificial intelligence and cancer medicine |
18.00 |
|
Discussion and conclusions |
Istituto Europeo di Oncologia S.r.l.
CME Provider (n. 207) e Segreteria Scientifica
Ieoedu.eventi@ieo.it
The webinar is fully funded by Associazione Italiana per la Ricerca sul Cancro (AIRC), project IG-14300 “Carbon ions boost followed by pelvic photon intensity modulated radiotherapy for high-risk prostate cancer”, registered at ClinicalTrials.gov (NCT02672449), approved by IEO R86/14-IEO 98.
MZ Congressi S.r.l.
Tel: 02 66802323 3421863400
Ieoedu.eventi@ieo.it