Checking date: 28/04/2023

Course: 2023/2024

Surgical Navigation and Imaging
Master in Machine Learning for Health (Plan: 480 - Estudio: 359)


Department assigned to the subject: Bioengineering Department

Type: Electives
ECTS Credits: 3.0 ECTS


Requirements (Subjects that are assumed to be known)
Biosignals and Bioimages Biomedical image processing (or equivalent course)
In this course, students will learn about the algorithms, methods and devices used in image-guided medical interventions: positioning systems, patient-image registration, 3D printing or augmented reality. The concepts will be presented from a theoretical point of view to then perform a laboratory practice where they will be used to solve a specific problem. The clinical application of these methods in laparoscopic surgery, maxillofacial surgery and traumatology will also be presented, as well as the possibilities for training and clinical simulation. The orientation of the course is mainly practical so that the knowledge learned will be demonstrated in a final group project.
Skills and learning outcomes
Description of contents: programme
1. Introduction. Course description. Historical background on surgical navigation. History of navigation and image guided surgery. 2. Tracking systems. Mechanical, optical and magnetic tracking systems: operating principles, advantages and limitations. 3. Image registration. Need and definition of the image registration.Landmark-based registration; methods based on surfaces and volumes: Procrustes, ICP, Mutual Information. Accuracy measurements and error estimation. 4. Clinical applications of navigation. Examples of applications in neurosurgery, orthopedic surgery and traumatology, training of clinical staff, acquisition and fusion of ultrasound, radiotherapy ... 5. Detection and improvement of workflow in surgery. Algorithms for estimation of workflow in surgery. Automatic analysis of video sequences. 6. Augmented reality in surgery. Technical bases of augmented reality and virtual systems. Required hardware. Application development tools. 7. Laparoscopy and robotics in surgery. Device requirements in endoscopy. Surgical microscope. Use of infrared image in surgery. 8. 3D printing in the clinical setting. Background on 3D printing. Printing technologies. From the image to the printed model. Utility of customized phantoms. Clinical applications. 9. Development tools in image-guided surgery. Libraries and protocols: PLUS, OpenIGTLink .. 3DSlicer environment with Python. Development of specific modules.
Learning activities and methodology
AF3 Theoretical practical classes AF4 Laboratory practices AF6 Team work AF7 Student individual work AF8 Partial and final exams Activity code total hours number presencial hours number non-presencial hours number AF3 84 84 0 AF4 63 63 0 AF6 90 0 90 AF7 222 0 222 AF8 9 9 0 TOTAL MATERIA 468 156 312
Assessment System
  • % end-of-term-examination 30
  • % of continuous assessment (assigments, laboratory, practicals...) 70
Calendar of Continuous assessment
Basic Bibliography
  • Terry Peters; Kevin Cleary Editors. Image-Guided Interventions: Technology and Applications. Springer. 2008
Recursos electrónicosElectronic Resources *
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The course syllabus may change due academic events or other reasons.