#radiomics
6 papers · 1 filter
Negative controls reveal volume-driven confounding in radiomics and imaging foundation model features
Katy L. Scott, Sejin Kim, Joshua Siraj +6
The paper presents READII-2-ROQC, an open‑source framework that uses volume‑preserving negative controls to test whether radiomic and deep imaging features capture genuine spatial…
A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor
Yin Lin, Elena De Martin, Giacomo Conte +6
The paper introduces a web‑based visual analytics platform that integrates cohort management, radiomic feature extraction, and guarded inference with pre‑trained machine learning m…
Multi-scale radiomics in pelvic MRI for endometriosis subtyping: highlighting data heterogeneity constraints
Eliot Leguy, Chloe Mallet, Nicolas Normand +1
The paper evaluates a radiomics pipeline on pelvic MRI to subtype endometriosis, comparing multi‑scale feature representations and showing modest classification performance but lim…
Comparing the Performance of Foundation Model Derived Embeddings with Traditional Approaches for Distant Metastasis Prediction in Head and Neck Cancer
Erich Schmitz, Meixu Chen, Bowen Jing +1
The study evaluates CT foundation model embeddings for predicting distant metastasis in head and neck cancer and finds they outperform traditional radiomics and deep‑learning featu…
SARFA: Segment Anything with Radiomic Feature Alignment
Tyler Ward, Abdullah Imran
The paper introduces SARFA, a framework that improves ambiguous medical image segmentation by generating multiple candidate masks and aligning them with radiomic features using Fré…
Physically Aware Radiomics Without Interpolation: Disentangling Voxel Geometry and Signal Modification in CT and MRI
David Corral Fontecha, Juan Miranda Bautista, Pablo Menendez Fernández-Miranda +3
The paper introduces a radiomics framework that accounts for voxel spacing without resampling, preserving the original image signal and improving feature robustness in anisotropic…