D5.3 Deep Learning Master model and Radiomic Signatures

Mar 12, 2024 | Deliverables

Deliverable 5.3, led by partner FCHAMPALIMAUD, contains the work performed by the ProCAncer-I
consortium on master models using radiomics and deep learning techniques. ’Master models’ — models
which can act as a foundation for other models — were developed for radiomics for all relevant use cases
(UC2, UC3, UC5, UC6, UC7a, UC7b and UC8) through the development of consistent and robust pipelines,
while deep learning was used only for UC1, UC2 and UC5 due to its more demanding data requirements.
Radiomics master models were developed by three partners (FCHAMPALIMAUD, FORTH and CNR), while
deep learning master models were developed and investigated by six different partners (FCHAMPALIMAUD,
CNR, FORTH, ADVANTIS, FPO, QUIBIM). Through this approach, several aspects of deep learning models
were investigated and consistent approaches and trends were identified. We finally note that the concept of
a ’master model’ is similar to that of a foundation model; in that light, this deliverable reflects that insight.
We describe the work in terms of foundation models and provide an overview of all experiments performed
to arrive at foundation models.

Highlights

ProCAncer-I at the ECR 2025 in Vienna

ProCAncer-I at the ECR 2025 in Vienna

ProCAncer-I will organise a Dedicated Session on the project during the European Congress of Radiology 2025 on the 26th of February 2025, at 15.00-16.00, with the title "ProCAncer-I: an AI platform integrating multiparametric MRI and AI models" where we will present...

ProCAncer-I at the EMUC24 in Lisbon

ProCAncer-I at the EMUC24 in Lisbon

The progress of major trials, the advent of artificial intelligence (AI), and interdisciplinary best practices were discussed at the 16th European Multidisciplinary Congress on Urological Cancers (EMUC24). The congress took place from the 7th to 10th of November 2024...

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