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Sight to touch: 3D diffeomorphic deformation recovery with mixture components for perceiving forces in robotic-assisted surgery
Avilés Rivero, Angélica; Alsaleh, Samar M.; Casals Gelpi, Alicia
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial; Universitat Politècnica de Catalunya. GRINS - Grup de Recerca en Robòtica Intel·ligent i Sistemes
Robotic-assisted minimally invasive surgical sys-tems suffer from one major limitation which is the lack of interaction forces feedback. The restricted sense of touch hinders the surgeons’ performance and reduces their dexterity and precision during a procedure. In this work, we present a sensory substitution approach that relies on visual stimuli to transmit the tool-tissue interaction forces to the operating surgeon. Our approach combines a 3D diffeomorphic defor-mation mapping with a generative model to precisely label the force level. The main highlights of our approach are that the use of diffeomorphic transformation ensures anatomical structure preservation and the label assignment is based on a parametric form of several mixture elements. We performed experimentations on both ex-vivo and in-vivo datasets and offer careful numerical results evaluating our approach. The results show that our solution has an error measure less than 1mm in all directions and an average labeling error of 2.05%. It can also be applicable to other scenarios that require force feedback such as microsurgery, knot tying or needle-based procedures.
Peer Reviewed
-Àrees temàtiques de la UPC::Informàtica::Robòtica
-Biomechanics
-Three dimensional imaging in medicine
-Robotics in medicine
-Vision based force estimation
-Robot assisted minimally invasive surgery
-Topology preservation
-Biomecànica
-Imatges tridimensionals en medicina
-Robòtica en medicina
Artículo - Versión presentada
Objeto de conferencia
Institute of Electrical and Electronics Engineers (IEEE)
         

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