Department of Electrical and Computer Engineering

Ready to unlock the full potential of medical imaging data and build powerful AI-driven analysis workflows? Join us for an interactive seminar exploring how MATLAB supports end-to-end medical image analysis across MRI, CT, X-ray, ultrasound, and PET/SPECT data.

This hands-on session will walk through the complete workflow—from importing DICOM and NIfTI volumes with spatial metadata to interactive 2D and 3D visualization, cinematic rendering, preprocessing, registration, segmentation, labeling, and quantitative analysis. You’ll see live demonstrations of lung tissue segmentation with the Medical Image Labeler, classical methods such as active contours, automated organ segmentation with MONAI Label, and radiomics workflows for extracting standardized shape, intensity, and texture features. We will also cover building and evaluating machine learning models to classify tumors as benign or malignant.
In addition, the seminar addresses real-world scale challenges, including blocked image processing for whole-slide images that exceed memory limits, masking and multi-resolution strategies, and the use of pretrained deep learning models such as Cellpose to segment and count cells at scale.

Whether you are new to medical image analysis or looking to streamline advanced AI workflows, this session will provide practical tools and immediately applicable techniques to move your research forward.

📅 Wednesday, March 11, 2026
📍 Location: Engineering Hall 106B8
🕒 12:00 - 01:00 PM

Lunch will be provided. Bring your notes and drink