N. Loução

most citedA multicenter study on radiomic features from T

_{2}

-weighted images of a customized MR pelvic phantom setting the basis for robust radiomic models in clinics

5 citations · 5 across the 2 of their papers we have counts for

collaborators

2 papers

eess.IV2024

Counterfactual MRI Data Augmentation using Conditional Denoising Diffusion Generative Models

Pedro Morão, Joao Santinha, Yasna Forghani +3

Deep learning (DL) models in medical imaging face challenges in generalizability and robustness due to variations in image acquisition parameters (IAP). In this work, we introduce…

eess.IV2020★ 5 cited

A multicenter study on radiomic features from T $_{2}$ -weighted images of a customized MR pelvic phantom setting the basis for robust radiomic models in clinics

Linda Bianchini, Joao Santinha, Nuno Loução +7

In this study we investigated the repeatability and reproducibility of radiomic features extracted from MRI images and provide a workflow to identify robust features. 2D and 3D T$_…

Counterfactual MRI Data Augmentation using Conditional Denoising Diffusion Generative Models

A multicenter study on radiomic features from T2​-weighted images of a customized MR pelvic phantom setting the basis for robust radiomic models in clinics

A multicenter study on radiomic features from T $_{2}$ -weighted images of a customized MR pelvic phantom setting the basis for robust radiomic models in clinics