Module 5 Overview#
Theme#
Segmentation and measurement
Essential Question#
How do models support localization and quantification?
Module Components#
Book prose: conceptual framing, domain scenario, methods, and failure modesAssignment: evidence-backed production of a specific artifactSlides: presentation sequence for seminar or lecture deliveryNarration: spoken version of the slide flowInstructor notes: facilitation plan, discussion prompts, and grading cuesRubric: criteria for evaluating the module artifactNotebook: executable lab aligned with the module theme using synthetic 8x8 grayscale image arrays with a small bright lesion pattern and non-lesion variation
Module Artifact#
imaging model evidence packet with preprocessing notes, validation limits, and clinical handoff risks focused on segmentation and measurement: Prototype or analyze a segmentation workflow.
Professional Setting#
Students work as if advising a radiology service deciding whether an imaging AI should advance from retrospective review to supervised pilot use. Their work must be intelligible to radiologist, imaging technician, compliance officer, and patient safety lead.