Surgical Simulation, Planning and Image Guided Surgery
From left to right: Enrique J. Gómez Aguilera, Borja Rodríguez Vila, Ignacio Oropesa García, xx, Jaime Tarjuelo Gutiérrez, Pablo Fontanilla Arranz, Luis Miguel González Rivas, Roman Calafati Ascheri, Jorge García Novoa, Patricia Sánchez González, xx, xx, xx, Marta Luna Serrano.
Target: The development of new techniques, methods and algorithms for the acquisition, processing and analysis of medical images and laparoscopic videos for surgical training, assessment and image guided surgical applications. Strategic partners include European Research Centers and Hospitals such as the Jesús Usón Minimally Invasive Surgery Centre (Cáceres, Spain), SINTEF (Trondheim, Norway), the Delft University of Technology (Delft, The Netherlands) or the Hospital La Princesa (Madrid, Spain).
Description: Minimally invasive surgery (MIS) has become a procedural standard for many surgical sub-specialties. These techniques forgo the traditional approach of open interventions, allowing surgeons to perform surgeries through minimal incisions in the patient’s body. In general, MIS interventions are less painful for the patient and more cosmetically pleasing; have fewer post-operative complications associated, decrease morbidity and mortality, and can shorten hospital stays. The shift of paradigm comes at a price, and surgeons must learn to cope with a series of disadvantages related to their kinetic/sensorial perception and ergonomic disposition with respect to the surgical scenario: lack of depth perception, reduced tactile sensation, restriction and inversion of instruments’ movements or lack of hand-eye coordination, most prominently.
Specific working lines include:
- Adaptive radiotherapy in prostate cancer.
- Image-guided catheterization.
- Image guided liver interventions.
- Endoscopic video analysis.
- Segmentation and 3D reconstruction of the liver and its vascular structures.
- Technology enhanced learning for MIS surgical training.
- Virtual reality surgical simulators.
- Surgical skills’ assessment based on motion analysis.
Techniques: Medical image segmentation, automatic landmark detection, non-rigid image registration, classification of anatomical structures, quantification of volume variations, video-based tracking, video-based 3D reconstruction, visualization technologies, system integration, motion analysis, supervised classification of surgical performance.
Infrastructure: Virtual reality simulator, haptics system, Microsoft Kinect, 3D position electromagnetic sensors, surgical enhanced box-trainer, MIS training and assessment tasks, endoscopic video analysis workstation, VR platform for aortic catheterization, 3D registration and medical image fusion workstation, image visualization and processing SW (Matlab, ITK, VTK, Qt, 3D slicer, Paraview, Dicomworks, Blender, Irrlicht).