PROGRAMME

15.00

 

Welcome and lntroduction
R. Orecchia, B.A Jereczek-Fossa

SESSION 1
Chairs: B.A Jereczek-Fossa, M. Cremonesi

15.10

 

Optimization of structural similarity in image analysis and visual quality
D. La Torre

15.25

 

How can we make radiomics and deep learning explainable?
S.Tanadini

15.40

 

Discussion

15.55

 

Feature Engineering versus Feature Learning for Radiomics
A. Bhalerao

16.10

 

Radiomics and rectal cancer: a promising application
L. Boldrini

16.25

 

Discussion

SESSION 2
Chairs: G. Petralia, E. De Momi

16.40

 

Radiomics and hadrontherapy: where we are now?
G. Baroni

16.55

 

Radiomics and whole-body MRI
A. Colombo

17.05

 

Discussion

17.20

 

Autosegmentation strategies in prostate cancer
M. Pepa

17.30

 

Deep Learning in prostate cancer radiomics
J.Isaksson

17.40

 

Prostate cancer radiomics in the clinics: ready for prime time?
S. Volpe
Clinical Applications in high-risk prostate cancer (AIRC IG-14300)
G. Marvaso

17.50

 

Artificial intelligence and cancer medicine
G. Curigliano

18.00

 

Discussion and conclusions
B.A. Jereczek-Fossa

CME Provider

Istituto Europeo di Oncologia S.r.l.
CME Provider (n. 207) e Segreteria Scientifica
Ieoedu.eventi@ieo.it

With the Endorsement of


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.

Organising Secretariat

MZ Congressi S.r.l.
Tel: 02 66802323 3421863400
Ieoedu.eventi@ieo.it