On the spine of a PDE surface

yesThe spine of an object is an entity that can characterise the object¿s topology and describes the object by a lower dimension. It has an intuitive appeal for supporting geometric modelling operations. The aim of this paper is to show how a spine for a PDE surface can be generated. For the purpose of the work presented here an analytic solution form for the chosen PDE is utilised. It is shown that the spine of the PDE surface is then computed as a by-product of this analytic solution. This paper also discusses how the of a PDE surface can be used to manipulate the shape. The solution technique adopted here caters for periodic surfaces with general boundary conditions allowing the possibility of the spine based shape manipulation for a wide variety of free-form PDE surface shapes

Automated Identification and Measurement of Objects via Populations of Medial Primitives, with Application to Real Time 3D Echocardiography

We suggest that identification and measurement of objects in 3D images can be automatic, rapid and stable, based on the statistical properties of populations of medial primitives sought throughout the image space. These properties include scale, orientation, endness, and medial dimensionality. The property of medial dimensionality is 0.0 for the sphere, 1.0 for the cylinder, and 2.0 for the slab, with non-integer dimensionality also possible. Endness results at the cap of a cylinder or the edge of a slab. The values of these medial properties at just a few locations provide an intuitive and robust model for complex shape. For example, the left ventricle during systole can be described as a large cylinder with an apical cap at one end, a slab-like mitral valve at the other (closed during systole), and appropriate interrelations among components in terms of their scale, orientation, and location. To look for such geometric components we extract populations of medial primitives we call co..

Detection of objects by integrating watersheds and critical point analysis

This paper presents an improved method for detection of "significant" low-level objects in medical images. Information derived from watershed regions is used to select and refine saddle points in the discrete domain and to construct the watersheds & watercourses (ridges and valleys). The method overcomes previous topological problems where multiple redundant saddle points are detected in digital images. We also demonstrate an improved method of pruning the tessellation from which salient objects are defined. Preliminary evaluation was based on theoretical analysis, visual inspection of a set of medical images, and human observer experiments with promising result

A New Approach to 3D Sulcal Ribbon Finding from MR Images

. Sulcal medial surfaces are 3D thin convoluted ribbons embedded in cortical sulci, and they provide distinctive anatomical features of the brain. Here we propose a new approach to automatic intrasulcal ribbon finding, following our work on cortex segmentation with coupled surfaces via level set methods, where the outer cortical surface is embedded as the zero level set of a high-dimensional distance function. Through the utilization of this distance function, we are able to formulate the sulcal ribbon finding problem as one of surface deformation, thus avoiding possible control problems in other work using sliding contour models. Using dynamic programming and deformable surface models, our method requires little manual intervention and results parameterized sulcal ribbon surfaces in nearly real-time. Though a natural follow up to our earlier segmentation work, we describe how it can be applied with general segmentation methods. We also present quantitative results on 15 MR brain image..