Our Products
Advanced tools for medical imaging research and radiomics analysis.
Product List
Radiuma
An open-source platform for standardized radiomics analysis, medical image visualization, and machine learning workflows.
Radiuma is a free, open-source software specialized for visualization, processing, segmentation, registration, fusion and analysis of medical and biomedical images, including radiomics and machine learning analysis. Radiuma is a major, entirely-revamped upgrade to the original SERA (Matlab-based), now built on Python for broader accessibility and community contribution. It enables standardized and reproducible radiomic feature extraction in compliance with the Image Biomarker Standardization Initiative (IBSI 1.0), and implements image filters standardized against IBSI 2.0.
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PySERA
PySERA (Python‑based Standardized Extraction for Radiomics Analysis) is a comprehensive Python library and standalone radiomics engine supporting IBSI‑standardized handcrafted features (557 total) and deep learning features (ResNet50, VGG16, DenseNet121). With a single‑function API, automatic multip
PySERA (Python-based Standardized Extraction for Radiomics Analysis), published in "PySERA" is a comprehensive Python library for radiomics feature extraction from medical imaging data. It provides a simple, single-function API with built-in multiprocessing support, comprehensive report capabilities, and optimized performance through OOP architecture, RAM optimization, and CPU-efficient parallel processing. PySERA supports both traditional handcrafted radiomics (557 features including 487 IBSI-compliant, 60 diagnostic, and 10 moment-invariant features) and deep learning-based feature extraction using pre-trained models like ResNet50, VGG16, and DenseNet121.
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AllMetrics
AllMetrics is an open‑source Python library designed to standardize machine learning metric evaluation. It provides consistent metric implementations, robust data validation, and a modular API supporting regression, classification, clustering, segmentation, and image‑to‑image translation tasks.
AllMetrics is an open-source, Python-native library designed to solve the critical problem of inconsistency in machine learning performance evaluation. While existing libraries are often fragmented and plagued by “Implementation Differences” (ID) and “Reporting Differences” (RD), AllMetrics provides a single, robust ecosystem for standardized metric computation. Designed for scalability and precision, our modular API supports a comprehensive suite of tasks—including regression, classification, clustering, segmentation, and image-to-image translation. By integrating rigorous input validation mechanisms and reconciling computational logic across disparate frameworks (Python, MATLAB, and R), AllMetrics ensures that your model performance reports are not only reproducible but mathematically trustworthy. Whether you are operating in healthcare, finance, or real estate, AllMetrics eliminates evaluation ambiguity, allowing you to focus on model optimization rather than metric validation.
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