André Guéziec

Progressive forest split compression

In this paper we introduce the Progressive Forest Split (PFS) representation, a new adaptive refinement scheme for storing and transmitting manifold triangular meshes in progressive and highly compressed form. As in the Progressive Mesh (PM) method of Hoppe, a triangular mesh is represented as a low resolution polygonal model followed by a sequence of refinement operations, each one specifying how to add triangles and vertices to the previous level of detail to obtain a new level. The PFS format shares with PM and other refinement schemes the ability to smoothly interpolate between consecutive levels of detail. However, it achieves much higher compression ratios than PM by using a more complex refinement operation which can, at the expense of reduced granularity, be encoded more efficiently. A forest split operation doubling the number n of triangles of a mesh requires a maximum of approximately 3:5n bits to represent the connectivity changes, as opposed to approximately (5 + log2(n))n bits in PM. We describe algorithms to efficiently encode and decode the PFS format. We also show how any surface simplification algorithm based on edge collapses can be modified to convert single resolution triangular meshes to the PFS format. The modifications are simple and only require two additional topological tests on each candidate edge collapse. We show results obtained by applying these modifications to the Variable Tolerance method of Gueziec. CR

Computer-integrated revision total hip replacement surgery: concept and preliminary results

This paper describes an ongoing project to develop a computer-integrated system to assist surgeons in revision total hip replacement (RTHR) surgery. In RTHR surgery, a failing orthopedic hip implant, typically cemented, is replaced with a new one by removing the old implant, removing the cement and fitting a new implant into an enlarged canal broached in the femur. RTHR surgery is a difficult procedure fraught with technical challenges and a high incidence of complications. The goals of the computer-based system are the significant reduction of cement removal labor and time, the elimination of cortical wall penetration and femur fracture, the improved positioning and fit of the new implant resulting from precise, high-quality canal milling and the reduction of bone sacrificed to fit the new implant. Our starting points are the ROBODOC system for primary hip replacement surgery and the manual RTHR surgical protocol. We first discuss the main difficulties of computer-integrated RTHR surgery and identify key issues and possible solutions. We then describe possible system architectures and protocols for preoperative planning and intraoperative execution. We present a summary of methods and preliminary results in CT image metal artifact removal, interactive cement cut-volume definition and cement machining, anatomy-based registration using fluoroscopic X-ray images and clinical trials using an extended RTHR version of ROBODOC. We conclude with a summary of lessons learned and a discussion of current and future work.

Appying Shape from Lighting Variation to Bump Map Capture

We describe a system for capturing bump maps from a series of images of an object from the same view point, but with varying, known, illumination. Using the illumination information we can reconstruct the surface normals for a variety of, but not all, surface finishes and geometries. The system allows an existing object to be rerendered with new lighting and surface finish without explicitly reconstructing the object geometry.

Cutting and stitching: converting sets of polygons to manifold surfaces

Many real-world polygonal surfaces contain topological singularities that represent a challenge for processes such as simplification, compression, and smoothing. We present an algorithm that removes singularities from nonmanifold sets of polygons to create manifold (optionally oriented) polygonal surfaces. We identify singular vertices and edges, multiply singular vertices, and cut through singular edges. In an optional stitching operation, we maintain the surface as a manifold while joining boundary edges. We present two different edge stitching strategies, called pinching and snapping. Our algorithm manipulates the surface topology and ignores physical coordinates. Except for the optional stitching, the algorithm has a linear complexity and requires no floating point operations. In addition to introducing new algorithms, we expose the complexity (and pitfalls) associated with stitching. Finally, several real-world examples are studied.

Locally toleranced surface simplification

We present a technique for simplifying a triangulated surface. Simplifying consists of approximating the surface with another surface of lower triangle count. Our algorithm can preserve the volume of a solid to within machine accuracy; it favors the creation of near-equilateral triangles. We develop novel methods for reporting and representing a bound to the approximation error between a simplified surface and the original, and respecting a variable tolerance across the surface. A different positive error value is reported at each vertex. By linearly blending the error values in between vertices, we define a volume of space, called the error volume, as the union of balls of linearly varying radii. The error volume is built dynamically as the simplification progresses, on top of preexisting error volumes that it contains. We also build a tolerance volume to forbid simplification errors exceeding a local tolerance. The information necessary to compute error values is local to the star of a vertex; accordingly, the complexity of the algorithm is either linear or in O(n log n) in the original number of surface edges, depending on the variant. We extend the mechanisms of error and tolerance volumes to preserve during simplification scalar and vector attributes associated with surface vertices. Assuming a linear variation across triangles, error and tolerance volumes are defined in the same fashion as for positional error. For normals, a corrective term is applied to the error measured at the vertices to compensate for nonlinearities.

A framework for streaming geometry in VRML

We introduce a framework for streaming geometry in VRML that eliminates the need to perform complete downloads of geometric models before starting to display them. This framework for the progressive transmission of geometry has three main parts, as follows: 1) a process to generate multiple levels-of-detail (LODs); 2) a transmission process (preferably in compressed form); and 3) a data structure for receiving and exploiting the LODs generated in the first part and transmitted in the second. The processes in parts 1 and 2 have already received considerable attention. We concentrate on a solution for part 3. Our basic contribution is a flexible LOD storage scheme, which we refer to as a progressive multilevel mesh. This scheme, primarily intended as a data structure in memory, has a low memory footprint and provides easy access to the various LODs (thus suitable for efficient rendering). This representation is not tied to a particular automated polygon reduction tool. In fact, we can use the output of any polygon reduction algorithm based on vertex clustering (including the edge collapse operations used in several algorithms). The progressive multilevel mesh complements compression techniques such as those developed by M. Deering (1995), H. Hoppe (1996) or G. Taubin et al. (1998). We discuss the integration of some of these compression techniques. However, for the sake of simplicity, we use a simple file format to describe the algorithm.

Simplicial maps for progressive transmission of polygonal surfaces

We present a new method for (1) automatically generating multiple Levels Of Detail (LODs) of a polygonal surface, (2) progressively loading, or transmitting, and displaying a surface, and for (3) changing interactively the LOD when displaying. We build the LODs using any algorithm that performs edge collapses and certain vertex removals to simplify surfaces, and provides an ordered list of ordered vertex pairs (edge collapse specifications). We propose a Surface Partition for encoding surface LODs: we define vertex and triangle levels during simplification; vertices and triangles are partitioned and sorted according to their level, and are passed to the display algorithm in decreasing level order, one level at a time, together with a vertex representatives array. Each level of vertices and triangles, together with higher levels and the vertex representatives, form a valid surface. The vertex representatives array encodes a succession of simplicial maps between the highest resolution LOD and other LODs. We propose a data structure using a Directed Acyclic Graph (DAG) for recording a partial ordering among edge collapses, and varying the LODs across the surface. We describe an implementation of our method in VRML. Key-words : Simplicial Map, Edge Collapse, Vertex and Triangle Levels, Surface Levels of Detail, Surface Partition, Progressive Transmission and Display, Dynamic Simplification.

Medical image registration using geometric hashing

To carefully compare pictures of the same thing taken from different views, the images must first be registered, or aligned so as to best superimpose them. Results show that two geometric hashing methods, based respectively on curves and characteristic features, can be used to compute 3D transformations that automatically register medical images of the same patient in a practical, fast, accurate, and reliable manner.

Providing visual information to validate 2-D to 3-D registration

This paper addresses a key issue of providing clinicians with visual information to validate the accuracy of 2-D/3-D registration for robot-assisted total hip replacement (THR) surgery. Although numerous registration approaches have been presented, the topic of registration validation has scarcely been addressed in the literature. In practice, clinicians rely on post-operative X-rays to assess the accuracy of implant placement. Motivated by this, we simulate a set of post-operative X-ray images by superimposing the implant positioned pre-operatively onto the intra-operatively collected and calibrated images of the femur, through a transformation computed by the 2-D/3-D registration. With these images, a judgment on the registration accuracy can be made. In addition, this paper introduces methods for superimposing pre-operative data on intra-operative X-ray images that were not corrected for distortion, by applying the same image distortion to the data. This paper also introduces a new framework for incorporating surface normals in the objective function for registration. A comparison between marker-based and image-based registration is conducted. The advantage of our approach is that the simulated post-operative X-ray images are very familiar to clinicians and, therefore, easy for them to interpret. As an added benefit, this technique provides new means for comparing the marker-based and image-based registration for robot-assisted THR surgery. This approach can be extended to other interventions where intra-operative images are used for registration.

An overview of computer-integrated surgery at the IBM Thomas J. Watson Research Center

This paper describes some past and current research activities at the IBM Thomas J. Watson Research Center. We begin with a brief overview of the emerging field of computer-integrated surgery, followed by a research strategy that enables a computer-oriented research laboratory such as ours to participate in this emerging field. We then present highlights of our past and current research in four key areas—orthopaedics, craniofacial surgery, minimally invasive surgery, and medical modeling—and elaborate on the relationship of this work to emerging topics in computer-integrated surgery.