Introduction
What is isciml?
isciml is short for Imaging using SCIentific Machine Learning. isciml is a powerful command-line tool designed to solve 3D non-invasive imaging problems using physics-informed artificial intelligence. This versatile tool offers a range of capabilities through its various subcommands and options, making it an ideal solution for researchers, engineers, and data scientists working in fields such as medical imaging, geophysics, and materials science.
Key Features
Command-line Interface: isciml provides a user-friendly command-line interface, allowing for easy integration into existing workflows and scripts.
Containerization: The tool is containerized, ensuring consistency across different environments and simplifying deployment and reproducibility.
Input Model Generation: isciml can generate input models, streamlining the setup process for various imaging scenarios.
Synthetic Data Generation: Utilizing advanced PDE solvers, isciml can create synthetic data for training and testing purposes.
Scalability: The tool is capable of generating data at scale, leveraging hundreds of cores for efficient processing.
Cloud and HPC Compatibility: isciml is designed to run seamlessly on both cloud platforms and High-Performance Computing (HPC) clusters, offering flexibility in computational resources.
Multi-GPU Training: Deep learning models can be trained using multiple GPUs, significantly reducing training time for complex imaging problems.
Key Benefits
Efficiency: As a command-line tool, isciml enables rapid execution and easy integration into automated workflows, saving time and reducing manual intervention.
Portability: The containerized nature of isciml ensures consistent performance across different computing environments, from personal workstations to large-scale cloud infrastructures.
Flexibility: With its ability to generate input models and synthetic data, isciml provides researchers with a complete toolkit for exploring various imaging scenarios without relying on external software.
Scalability: isciml's capacity to utilize hundreds of cores for data generation and multiple GPUs for model training allows users to tackle large-scale imaging problems efficiently.
Resource Optimization: The tool's compatibility with both cloud platforms and HPC clusters enables users to choose the most cost-effective and suitable computational resources for their specific needs.
Accelerated Research: By combining physics-informed AI with powerful computational capabilities, isciml accelerates the development and testing of novel imaging techniques and algorithms.
Reproducibility: The containerized environment and command-line interface facilitate reproducible research, allowing easy sharing and verification of results among collaborators and the scientific community.
Whether you're working on medical diagnostics, subsurface imaging, or non-destructive testing, isciml provides a comprehensive suite of tools to tackle challenging 3D non-invasive imaging problems. In the following sections, we'll explore the various subcommands and options available in isciml, along with detailed usage instructions and examples.
Last updated
