From Scan to Screen: Visualizing Medical DICOM Data with Python скачать в хорошем качестве

From Scan to Screen: Visualizing Medical DICOM Data with Python

In this technical talk, I share how breaking my knee while bouldering led to an exploration of medical imaging visualization. After suffering a tibial plateau fracture (Schatzker type IV) requiring osteosynthesis with titanium plates and screws, I turned my recovery time into a deep dive into DICOM data processing and 3D visualization techniques. *Technical Overview:* This presentation covers the complete pipeline from raw medical imaging data to interactive 3D visualizations. We explore CT scan fundamentals, including Hounsfield units and their density mappings (air at -1000 HU, soft tissue 0-300 HU, bone 300-1000 HU, and titanium at ~3000 HU). The talk demonstrates practical Python implementations for parsing DICOM files, converting to NumPy arrays, and using NRRD datasets for volumetric rendering. *Key Topics Covered:* • DICOM file format structure and metadata extraction • CT vs MRI imaging principles and data characteristics • Volumetric rendering techniques: ISO surface extraction, Maximum Intensity Projection (MIP), and ray tracing • WebGL shader implementation for real-time 3D visualization • Transfer functions and opacity mapping for medical data • Handling imaging artifacts from metal implants *Technical Stack:* Python (NumPy, pydicom), JavaScript (Three.js), WebGL shaders, NRRD format *Chapters:* 00:00 Introduction 00:20 Bouldering and overhangs 02:17 What now? 04:22 Medical Imaging 04:49 CT imaging 10:58 NRRD format 17:00 Volumetric rendering 29:33 MRI imaging 31:47 Q&A 48:02 Conclusion 48:13 End Code available at: [repository link]