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Biomedical subjects

M A González Ballester

Publications and source records attributed to M A González Ballester.

2 recordsLinked to original sources

Computer-assisted ankle joint arthroplasty using bio-engineered autografts.

Bio-engineered cartilage has made substantial progress over the last years. Preciously few cases, however, are known where patients were actually able to benefit from these developments. In orthopaedic surgery, there are two major obstacles between in-vitro cartilage engineering and its clinical application: successful integration of an autologuous graft into a joint and the high cost of individually manufactured implants. Computer Assisted Surgery techniques can potentially address both issues at once by simplifying the therapy, allowing pre-fabrication of bone grafts according to a shape model, individual operation planning based on CT images and providing optimal accuracy during the intervention. A pilot study was conducted for the ankle joint, comprising a simplified rotational symmetric bone surface model, a dedicated planning software and a complete cycle of treatment on one cadaveric human foot. The outcome was analysed using CT and MRI images; the post-operative CT was further segmented and registered with the implant shape to prove the feasibility of computer assisted arthroplasty using bio-engineered autografts.

Ankle Joint↗

Segmentation and measurement of brain structures in MRI including confidence bounds.

The advent of new and improved imaging devices has allowed an impressive increase in the accuracy and precision of MRI acquisitions. However, the volumetric nature of the image formation process implies an inherent uncertainty, known as the partial volume effect, which can be further affected by artifacts such as magnetic inhomogeneities and noise. These degradations seriously challenge the application to MRI of any segmentation method, especially on data sets where the size of the object or effect to be studied is small relative to the voxel size, as is the case in multiple sclerosis and schizophrenia. We develop an approach to this problem by estimating a set of bounds on the spatial location of each organ to be segmented. First, we describe a method for 3D segmentation from voxel data which combines statistical classification and geometry-driven segmentation; then we discuss how the partial volume effect is estimated and object measurements are obtained. A comprehensive validation study and a set of results on clinical applications are also described.

Algorithms↗