Liver biomechanical model for virtual palpation.

Palpation is a diagnostic technique used for evaluating physical properties of abdominal tissues and organs. The emulation of this procedure using virtual simulators is challenging due to trades between realism and interactivity. In this paper a virtual palpation system of the liver is proposed using a polyhedral mesh with a first order viscoelastic model defined in terms of its biomechanical properties extracted from experimental data. The hepatic tissue model is approximated to large deformations leading to a realistic haptic response of the procedure.

3D liver volume reconstructed for palpation training.

Virtual Reality systems for medical procedures such as the palpation of different organs, requires fast, robust, accurate and reliable computational methods for providing realism during interaction with the 3D biological models. This paper presents the segmentation, reconstruction and palpation simulation of a healthy liver volume as a tool for training. The chosen method considers the mechanical characteristics and liver properties for correctly simulating palpation interactions, which results appropriate as a complementary tool for training medical students in familiarizing with the liver anatomy.

Segmentación seiiautomática del volumen del hígado en imágenes de tomografía computriizada / Semi-Automatic Liver Volume Segmentation in Computed Tomography Images

El volumen del hígado es un parámetro determinante en cirugía para la extracción de tumores, trasplantes, y en tratamientos de regeneración. Generalmente, la estimación de este volumen se calcula a partir de segmentaciones manuales realizadas por especialistas, siendo éste un proceso tedioso y con poca reproducibilidad de sus resultados. En este trabajo se presenta un método semiautomático para la segmentación del volumen del hígado en imágenes de TAC. El método consiste en superponer manualmente una superficie de triángulos en las imágenes, y deformarla por medio de una ecuación de movimiento asociada a cada uno de sus vértices, para delimitar las fronteras del hígado. La dinámica de la superficie depende de información de intensidades y gradientes, y de relaciones de vecindad entre los vértices, hasta cumplir un número de iteraciones. Comparaciones entre las segmentaciones del método con las segmentaciones de referencia en 20 estudios de TAC, muestran la adaptabilidad de la superficie a la forma y fronteras difusas del hígado, dos de los principales problemas de la segmentación.

Liver volume is a significant parameter in surgery for tumor extraction, transplants, and regeneration treatments. Generally, the volume estimation is obtained from manual segmentations performed by specialists, resulting in a tedious process with low reproducibility. In this work a semi-automatic method for the liver volume segmentation in CT images is presented. The method consist in manually superimpose a triangular surface on the images, and use a movement equation associated to each vertex to deform the surface and delimit the liver boundaries. Surface dynamics depend on intensity and gradient information, and neighboring relationships between vertices, until a fixed number of iterations is reached. Comparison between the obtained results and reference segmentations in 20 CT scans, show the surface adaptability to the shape and the diffuse boundaries of the liver, two of the principal segmentation problems.