Normalization strategies in multi-center radiomics abdominal MRI: systematic review and meta-analyses

J Panic, A Defeudis, G Balestra… - IEEE open journal of …, 2023 - ieeexplore.ieee.org
Goal: Artificial intelligence applied to medical image analysis has been extensively used to
develop non-invasive diagnostic and prognostic signatures. However, these imaging …

[HTML][HTML] Progress of MRI in predicting the circumferential resection margin of rectal cancer: a narrative review

Y Ma, D Ma, X Xu, J Li, Z Guan - Asian Journal of Surgery, 2024 - Elsevier
Rectal cancer (RC) is the third most frequently diagnosed cancer worldwide, and the status
of its circumferential resection margin (CRM) is of paramount significance for treatment …

Towards semi-supervised multi-modal rectal cancer segmentation: A large-scale dataset and a multi-teacher uncertainty-aware network

Y Qiu, H Lu, J Mei, S Bao, J Xu - Expert Systems with Applications, 2024 - Elsevier
Rectal cancer is one of the most common malignant tumors of the digestive tract. Recently,
deep learning has attracted significant attention in computer-aided cancerous region …

Comparison between different approaches for the creation of the training set: how clustering and dimensionality impact the performance of a Deep Learning model

J Panic, A Defeudis, D Regge… - 2023 IEEE 23rd …, 2023 - ieeexplore.ieee.org
In the last years, Deep learning (DL) has become an active research topic in the field of
medical image analysis, in particular for the automatic segmentation of pathological …

[PDF][PDF] A Fully Automatic Multi-Vendor AI-System To Segment And Predict Resistance To Treatment Of Rectal Cancer On MRI

J Panic12, A Defeudis, L Vassallo, S Cirillo… - … OF THE WORLD …, 2024 - avestia.com
In this study, we developed and validated a fully automatic system based on pretreatment
MRI to predict resistance to therapy in rectal cancer patients using a multi-center and multi …