The Image Biomarker Standardization Initiative: Standardized Convolutional Filters for Reproducible Radiomics and Enhanced Clinical Insights

Whybra, P.; Zwanenburg, Alex; Andrearczyk, Vincent; Schaer, Roger; Apte, Aditya; Ayotte, Alexandre; Baheti, Bhakti; Bakas, Spyridon; Bettinelli, Andrea; Boellaard, Ronald; Boldrini, Luca; Buvat, Irène; Cook, Gary; Dietsche, Florian; Dinapoli, N.; S. Gabryś, Hubert; Goh, Vicky; Gückenberger, Matthias; Hatt, Mathieu; Hosseinzadeh, Mahdi; Iyer, Aditi; Lenkowicz, Jacopo; Ait Lhaj Loutfi, Mahdi; Löck, Steffen; Marturano, Francesca; Morin, Olivier; Nioche, Christophe; Orlhac, Fanny; Pati, Sarthak; Rahmim, Arman; Masoud Rezaeijo, Seyed; G Rookyard, Christopher; R. Salmanpour, Mohammad; Schindele, Andreas; Shiri, Isaac; Spezi, Emiliano; Tanadini‐Lang, Stephanie; Tixier, Florent; Upadhaya, Taman; Valentini, Vincenzo; J. M. van Griethuysen, Joost; Yousefirizi, Fereshteh; Zaidi, Habib; Müller, Henning; Vallières, Martin; Depeursinge, Adrien

doi:10.1148/radiol.231319

Public

The Image Biomarker Standardization Initiative: Standardized Convolutional Filters for Reproducible Radiomics and Enhanced Clinical Insights

Published in Radiology • Feb 1, 2024

Authors:

P. Whybra

Alex Zwanenburg

Vincent Andrearczyk

Abstract

Filters are commonly used to enhance specific structures and patterns in images, such as vessels or peritumoral regions, to enable clinical insights beyond the visible image using radiomics. However, their lack of standardization restricts reproducibility and clinical translation of radiomics decisi...

Subject

Reproducibility

Intraclass correlation

Medicine

Research Assistant

AI chat, annotations, notes & similar papers

Finding related papers...

Discussions

(0)

No comments yet

Be the first to share your thoughts!