🧠 Imaging Fusion
Imaging fusion is the process of combining two or more medical imaging datasets—such as MRI, CT, PET, or fMRI—into a single spatially aligned view, used for better diagnostic and surgical accuracy.
✅ Key Characteristics
- Uses software algorithms to align images from different modalities
- Can be rigid (bone-based) or non-rigid (deformable tissue modeling)
- Enhances visualization of anatomy, function, and pathology
- Essential in neuronavigation, oncology, and stereotactic surgery
⚙️ Common Fusion Combinations
| Modality 1 | Modality 2 | Purpose |
|---|---|---|
| MRI | CT | Combines soft tissue with bone detail for surgical planning |
| PET | MRI | Localizes metabolic activity within anatomical context |
| fMRI | MRI | Identifies functional brain areas prior to resection |
| CT | Intraop CT | Used in frameless stereotaxy and robotic navigation |
📌 Clinical Example
- “We fused the patient's MRI with intraoperative CT to align targets with robotic coordinates.”
🧠 Applications
- Deep Brain Stimulation (DBS)
- Tumor resection planning
- Epilepsy surgery
- Stereotactic biopsy or radiosurgery