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Near Real-Time Cutting. Paul F. Neumann. Dept. of Ophthalmology and Visual Sciences. College of Health and Human Development Sciences, University of Illinois at Chicago. Virtual Reality Surgical Simulators. Simulate the functionality of surgical instruments such as blades and

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Presentation Transcript
slide1

Near

Real-Time

Cutting

Paul F. Neumann

Dept. of Ophthalmology and Visual Sciences

College of Health and Human Development Sciences, University of Illinois at Chicago

slide2

Virtual Reality Surgical Simulators

  • Simulate the functionality
  • of surgical instruments
  • such as blades and
  • scissors
  • A general 3D cutting
  • algorithm is a one of
  • challenging problems.
  • Simulators must maintain
  • an interactive frame rate.

Dept. of Ophthalmology and Visual Sciences

College of Health and Human Development Sciences, University of Illinois at Chicago

slide3

Previous Cutting Algorithms

1988 Tearing (Terzopoulos and Fleischer)

1992 Particle Systems (Szeliski and Tonnesen)

1992 Radial Projection on FEM (Pieper et al.)

1995 2D FEM Template (Song and Reddy)

1997 3D FEM with Bilinear Cutting Plane (Mazura and Seifert)

1997 Boolean Operations (Delp et al.)

1998 Hybrid Elastic Model (Colin et al.)

My Goal: To develop an interactive cutting algorithm on a

mass-spring system with a polygonal surface.

Dept. of Ophthalmology and Visual Sciences

College of Health and Human Development Sciences, University of Illinois at Chicago

slide4

Mass-Spring System

  • Very popular PBM platform
  • Vertices as mass points
  • Edges as vector springs
  • Dynamic system which permits
  • insertions and deletions
  • Distributes mass appropriately
  • Conserves surface area

Dept. of Ophthalmology and Visual Sciences

College of Health and Human Development Sciences, University of Illinois at Chicago

slide5

Vector Springs

  • Invented by Alan Millman at EVL
  • Maintain their orientation and length
  • Easy to subdivide

Dept. of Ophthalmology and Visual Sciences

College of Health and Human Development Sciences, University of Illinois at Chicago

slide6

Algorithm Overview

1) Samples blade’s path.

2) Reconstructs the path with a series of parallelograms.

3) Intersects and subdivides springs and triangles.

4) Recomputes mass and spring stiffness coefficients.

Dept. of Ophthalmology and Visual Sciences

College of Health and Human Development Sciences, University of Illinois at Chicago

slide7

Reconstructing Cutting Path

  • Discretely samples path.
  • Drop samples if roughly co-planar.
  • Fit parallelogram through two selected samples by
  • averaging orientation and adding offset.
  • Parallelograms lag behind current position.

Dept. of Ophthalmology and Visual Sciences

College of Health and Human Development Sciences, University of Illinois at Chicago

slide8

Intersection

Dept. of Ophthalmology and Visual Sciences

College of Health and Human Development Sciences, University of Illinois at Chicago

slide9

Subdivision

Intersection

Spring

Subdivision

Triangle

Subdivision

Further

Subdivision

New interior springs must compute their rest direction

through vector addition of their neighbors.

Dept. of Ophthalmology and Visual Sciences

College of Health and Human Development Sciences, University of Illinois at Chicago

slide10

Mass Distribution:

Localized Approximation

  • Mass proportional to surface area
  • at rest.
  • New vertices and their neighbors
  • have their mass values
  • recomputed after subdivision.
  • Spring rest direction vectors
  • outline the undeformed triangle
  • area.

Dept. of Ophthalmology and Visual Sciences

College of Health and Human Development Sciences, University of Illinois at Chicago

slide11

Cutting Example

Dept. of Ophthalmology and Visual Sciences

College of Health and Human Development Sciences, University of Illinois at Chicago

slide12

Cutting Example

Dept. of Ophthalmology and Visual Sciences

College of Health and Human Development Sciences, University of Illinois at Chicago

slide13

Cutting Example

Dept. of Ophthalmology and Visual Sciences

College of Health and Human Development Sciences, University of Illinois at Chicago

slide14

Cutting Example

Dept. of Ophthalmology and Visual Sciences

College of Health and Human Development Sciences, University of Illinois at Chicago

slide15

Cutting Example

Dept. of Ophthalmology and Visual Sciences

College of Health and Human Development Sciences, University of Illinois at Chicago

slide16

Cutting Example

Dept. of Ophthalmology and Visual Sciences

College of Health and Human Development Sciences, University of Illinois at Chicago

slide17

Variations

Suction Cutter

Tearing

Scissors

Dept. of Ophthalmology and Visual Sciences

College of Health and Human Development Sciences, University of Illinois at Chicago

slide18

Video Tape

Dept. of Ophthalmology and Visual Sciences

College of Health and Human Development Sciences, University of Illinois at Chicago

slide19

Discussion

  • Geometry dependence.
  • Lag in response time.
  • Rounds to nearest vertex.
  • Collision Detection
  • Small parallelograms within a
  • triangle aren’t processed.

Dept. of Ophthalmology and Visual Sciences

College of Health and Human Development Sciences, University of Illinois at Chicago

slide20

More Information

A more detailed paper is included on

your Application cdrom.

Web Site:

www.bvis.uic.edu/paul/

CAL Demonstration right after session

Dept. of Ophthalmology and Visual Sciences

College of Health and Human Development Sciences, University of Illinois at Chicago

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