This comprehensive guide walks you through building a production-ready DICOM anonymization microservice using ASP.NET Core and Aspose.Medical, including architecture patterns, code examples, and best practices.
This guide demonstrates a complete workflow for preparing medical imaging datasets for AI research, including batch anonymization and conversion to JSON format for ingestion into ML pipelines.
Understanding DICOM file contents is essential for medical imaging development, troubleshooting, and quality assurance. This tutorial shows you how to build a comprehensive DICOM metadata viewer in C# that extracts and displays patient information, study details, and technical imaging parameters. What is DICOM Metadata? DICOM files contain two main components: pixel data (the actual image) and metadata (information about the image). Metadata includes: Patient demographics: Name, ID, birth date, sex Study information: Date, time, description, referring physician Series details: Modality, body part, imaging protocol Image parameters: Dimensions, pixel spacing, window/level settings Equipment information: Manufacturer, model, software version A metadata viewer helps developers inspect these attributes for debugging, validation, and data analysis. ...
