6 papers
Radiuma: A Unified Zero-Code Executable Graphical Workflow Generator for Reproducible and Shareable Medical Image Analysis and Machine Learning
Mohammad Salmanpour, Mehrdad Oveisi, Isaac Shiri +1
Medical image computing software is essential for identifying imaging biomarkers that can support diagnosis, prognosis, treatment planning, and clinical research. However, the lack…
PySERA: Open-Source Standardized Python Library for Automated, Scalable, and Reproducible Handcrafted and Deep Radiomics
Mohammad R. Salmanpour, Amir Hossein Pouria, Sirwan Barichin +5
Radiomics enables the extraction of quantitative biomarkers from medical images for precision modeling, but reproducibility and scalability remain limited due to heterogeneous soft…
Semi-Supervised Radiomics for Glioblastoma IDH Mutation: Limited Labels, Data Sensitivity, and SHAP Interpretation
Amir Hossein Pouria, Shahram Taeb, Somayeh Sadat Mehrnia +4
Glioblastoma (GBM) is an aggressive brain tumor in which IDH mutation status is a key prognostic biomarker, but traditional testing requires invasive biopsies, emphasizing the need…
Enhancement Without Contrast: Stability-Aware Multicenter Machine Learning for Glioma MRI Imaging
Sajad Amiri, Shahram Taeb, Sara Gharibi +6
Gadolinium-based contrast agents (GBCAs) are central to glioma imaging but raise safety, cost, and accessibility concerns. Predicting contrast enhancement from non-contrast MRI usi…
Robust Semi-Supervised CT Radiomics for Lung Cancer Prognosis: Cost-Effective Learning with Limited Labels and SHAP Interpretation
Mohammad R. Salmanpour, Amir Hossein Pouria, Sonia Falahati +7
Background: CT imaging is vital for lung cancer management, offering detailed visualization for AI-based prognosis. However, supervised learning SL models require large labeled dat…
AllMetrics: A Unified Python Library for Standardized Metric Evaluation and Robust Data Validation in Machine Learning
Morteza Alizadeh, Mehrdad Oveisi, Sonya Falahati +6
Machine learning (ML) models rely heavily on consistent and accurate performance metrics to evaluate and compare their effectiveness. However, existing libraries often suffer from…