New publications: Probabilistic Reasoning and Decision Making in Sensory-Motor Systems

In this book Miriam Amavizca, Christian Laugier, Emmanuel Mazer, Francois Leitner and my self contribute with the book chapter entitled:

3D human hip volume reconstruction with incomplete multimodal medical images

This work is within the context of Computer-assisted Orthopaedic Surgery (CAOS), in particular Total Hip Replacement (THR) surgery.

In conventional medical imagery, the patient’s anatomy is obtained from multiple two-dimensional (2D) medical images. In contrast to conventional medical imagery, image processing allows a three-dimensional (3D) visualization of the patient from a numerical model. The 3D representation adds visibility to the organs and makes them more perceptible. Surgical systems intervene to obtain the 3D representation of the organs and to use the model in the different stages of the patient’s medical treatment: preoperative (planning), operative (control) and post-operative (validation). In this way, the aim of CAS is to obtain more precise post-operative results according to the preoperative planning than can be achieved with conventional techniques.

We propose a methodology for obtaining a 3D patient’s hip model from 2D data and partial 3D data. The 2D data are obtained from one anteroposterior radiographic image, and the partial 3D data are obtained from echographic images. All procedures are non-invasive, low cost and fast. The patient’s personalized model is obtained by a “deformation” of a generic hip mesh. Control points are obtained from radiographic and echographic data.

"The book Probabilistic Reasoning and Decision Making in Sensory-Motor Systems by Pierre Bessiere, Christian Laugier and Roland Siegwart provides a unique collection of a sizable segment of the cognitive systems research community in Europe. It reports on contributions from leading academic institutions brought together within the European projects Bayesian Inspired Brain and Artifact (BIBA) and Bayesian Approach to Cognitive Systems (BACS). This fourteen-chapter volume covers important research along two main lines: new probabilistic models and algorithms for perception and action, new probabilistic methodology and techniques for artefact conception and development. The work addresses key issues concerned with Bayesian programming, navigation, filtering, modelling and mapping, with applications in a number of different contexts."