Courses / Biomedical Image Analysis
Module 5 of 7
Biomedical Image Analysis
Explore biomedical imaging from core modalities to advanced AI-powered techniques. This module covers imaging fundamentals, preprocessing, segmentation, feature extraction, and deep learning–based computer vision. Learners also examine emerging topics such as self-supervised learning, multimodal fusion, and federated learning, along with privacy, de-identification, and ethical image-handling practices.
Free
Format · Online
Start date · Aug 31, 2026
Duration · 2 weeks
Time · 5 hrs / week
Microskills · 7
CME credits · 11
What you will gain
Course Outcomes
Integration of AI techniques
Integrate AI and ML into healthcare research and clinical practice.
Real-world data application
Use real medical data and case studies to address healthcare challenges.
Practical AI skills
Work with code-free AI/ML tools — no programming knowledge needed.
Critical thinking
Analyze complex healthcare problems through AI-driven insights and methodologies.
What you will learn
Microskills in this Module
Each module covers 5 AI microskills plus one Scientific Rigor and Reproducibility (SRR) and one Responsible Conduct of Research (RCR) microskill.
- Landscape of biomedical imaging
- Biomedical image preprocessing and transformation
- Traditional biomedical image analysis
- Biomedical computer vision applications
- Advanced and emerging topics in biomedical imaging
- Consistency in biomedical image analysis
- Ethical and privacy implications of biomedical imaging
Meet your instructors
Expert Faculty from the University of Florida
Azra Bihorac MD, MS
Senior Associate Dean for Research Affairs · Director, IC3
Ruogu Fang PhD
Associate Professor, Biomedical Engineering
Wei Shao PhD
Asst. Professor, Department of Medicine
Pinaki Sarder PhD
Associate Professor, Department of Medicine
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Ready to enroll?
Free enrollment. No coding required. Two cohorts per year — Spring and Fall.