Showing papers by "Miguel Ángel González Ballester published in 2013"

Geometric steerable medial maps

Abstract: To provide more intuitive and easily interpretable representations of complex shapes/organs, medial manifolds should reach a compromise between simplicity in geometry and capability of restoring the anatomy/shape of the organ/volume. Existing morphological methods show excellent results when applied to 2D objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds from a theoretical and a practical point of view. First, we introduce a continuous operator for accurate and efficient computation of medial structures of arbitrary dimension. Second, we present a validation protocol for assessing the suitability of medial surfaces for anatomical representation in medical applications. We evaluate quantitatively the performance of our method with respect to existing approaches and show its higher performance for medical imaging applications in terms of medial simplicity and capability of reconstructing the anatomical volume.

Multiresolution Hierarchical Shape Models in 3D Subcortical Brain Structures

Abstract: Point Distribution Models (PDM) are one of the most extended methods to characterize the underlying population of set of samples, whose usefulness has been demonstrated in a wide variety of applications, including medical imaging. However, one important issue remains unsolved: the large number of training samples required. This problem becomes critical as the complexity of the problem increases, and the modeling of 3D multiobjects/organs represents one of the most challenging cases. Based on the 3D wavelet transform, this paper introduces a multiresolution hierarchical variant of PDM (MRH-PDM) able to efficiently characterize the different inter-object relationships, as well as the particular locality of each element separately. The significant advantage of this new method over two previous approaches in terms of accuracy has been successfully verified for the particular case of 3D subcortical brain structures.

Automated annotation removal in agar plates

Abstract: Agar plates are widely used in the biomedical field as a medium in which to artificially grow bacteria, algae or fungi. Agar plates (Petri dishes) are used routinely in microbiology laboratories in order to identify the type of micro-organism responsible for infections. Such diagnoses are based on counting the number and type of bacterial colonies growing in the Petri dish. The count of bacterial colonies is a time consuming task prone to human error, so interest in automated counting systems has increased in the recent years. One of the difficulties of automatizing the counting process is the presence of markers and annotations made in the lower part of the agar plate. Efficient removal of such markers can increase the accuracy of the bacterial counting system. This article introduces a fast method for detection, segmentation and removal of annotations in agar plates that improves the results of existing bacterial colony counting algorithms.

Surgical Workflow Analysis, Design and Development of an Image-Based Navigation System for Endoscopic Interventions

Abstract: Endoscopic interventions in the abdominal and thoracic cavity are often hampered by the difficulty to orient in the endoscopic view. This is due to the small field of view and the inhomogeneous illumination, but also because abdominal organs are highly deformable and subject to complex movements. The use of flexible endoscopes further complicates these issues. In the context of a multidisciplinary project involving clinical and technical teams, we report the definition of clinical requirements and surgical workflow of abdominal endoscopic interventions, and present the design and implementation of a planning and navigation system. Some of the implemented features include: segmentation, tracking, landmark-based navigation, and combined surface and volume rendering. Our system is based on open source libraries, and is flexible and applicable to other types of interventions.

Functional simulation of the cochlea for implant optimization

Abstract: Cochlear implantation is a surgical technique which aims to restore hearing in people with deep hearing loss. However, outcomes of the surgery still exhibit a large variability between patients. Among the factors that contribute to variability the most important are morphological differences in anatomical structures between patients and incorrect implant placements. In order to address these issues, it would be desirable to have a functional model of the cochlea which incorporates inter-patients variability and simulate electrode placement. To this end, we present a finite element model which captures the interaction between the cochlear partition, modeled as an elastic solid with finite deformation, and the perilymph fluid, modeled as a compressible, viscous fluid. Numerical results show that the membrane responds to changes in the stimulation frequencies.