Research Presentation Sessions: Artificial Intelligence & Machine Learning & Imaging Informatics

RPS 2505 - New frontiers for AI in prostate MRI

Lectures

1
Can AI for prostate MRI generalise to multiple centres and scanners?

Can AI for prostate MRI generalise to multiple centres and scanners?

07:00Aarti Shah, Stockbridge / UK

2
Thin-slice prostate MRI enabled by deep learning image reconstruction

Thin-slice prostate MRI enabled by deep learning image reconstruction

07:00Sebastian Gassenmaier, Tuebingen / DE

3
Prostate gland segmentation on prostate magnetic resonance images: an AI study using a U-net-based convolutional neural network

Prostate gland segmentation on prostate magnetic resonance images: an AI study using a U-net-based convolutional neural network

07:00Başak Ünverdi, Izmir / TR

4
Deep learning-based algorithm for prostate cancer detection on multi-vendor MRI scans, with a focus on how annotator variability affects algorithm performance

Deep learning-based algorithm for prostate cancer detection on multi-vendor MRI scans, with a focus on how annotator variability affects algorithm performance

07:00Gaspard d'Assignies, Paris / FR

5
Developing a machine learning radiomics-based model to predict clinically significant prostate cancer on multi-parametric MRI

Developing a machine learning radiomics-based model to predict clinically significant prostate cancer on multi-parametric MRI

07:00Arrigo Cattabriga, Bologna / IT

6
Prediction of clinically significant prostate cancer using machine learning models

Prediction of clinically significant prostate cancer using machine learning models

07:00Ömer Önder, Ankara / TR

7
Development and validation of an explainable AI-CAD system to predict high-aggressive prostate cancer: a multicentre radiomics study based on biparametric MRI

Development and validation of an explainable AI-CAD system to predict high-aggressive prostate cancer: a multicentre radiomics study based on biparametric MRI

07:00Katia Rocco, Turin / IT

8
Prediction of Gleason grade discordance by using machine learning methods

Prediction of Gleason grade discordance by using machine learning methods

07:00Irem Loc, Istanbul / TR

9
Moderation

Moderation

00:00Francesco Giganti, London / UK

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