📚 Syllabus & Course Curriculum
Data Science & Analytics
Module-by-module breakdown of AI-Powered Echocardiography: From 2D Echo to 3D Ventricular Reconstruction, from foundations to a certified capstone project.
Outline
Explore cardiac anatomy for imaging and the AHA 17‑segment model • Understand ultrasound physics, transducer types and standard echo views • Learn AI basics – supervised learning, CNNs, U‑Net and semantic segmentation • Navigate DICOM echo files with Weasis and inspect metadata using pydicom
Outline
Build and train a MONAI U‑Net model on the CAMUS dataset • Apply data‑augmentation pipelines specific to echo imaging • Run inference with EchoNet‑Dynamic for ejection‑fraction estimation • Evaluate models using Dice, Hausdorff distance and MAE metrics
Outline
Convert 2D masks to 3D geometry using biplane Simpson’s method and voxel stacking • Create 3D LV meshes with 3D Slicer & SlicerHeart, post‑process in MeshLab/ParaView • Assemble an end‑to‑end pipeline (DICOM → preprocessing → MONAI segmentation → VTK rendering → volume report) • Export models to ONNX, deploy a Gradio demo and containerise with Docker
Earn government-registered certification in AI-Powered Echocardiography: From 2D Echo to 3D Ventricular Reconstruction
e-Certificate and e-Marksheet issued on successful completion.
