liz marai 01/30/09 1 computational modeling and visualization for science liz marai computer science

41
Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science http:// vis.cs.pitt.edu

Upload: leonard-bernard-williamson

Post on 26-Dec-2015

225 views

Category:

Documents


0 download

TRANSCRIPT

Page 1: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

1

Computational Modeling and Visualization for

Science

Liz MaraiComputer Science

http://vis.cs.pitt.edu

Page 2: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

2

What is Computer Science?

• (… the study of computers?)

• (… the art of programming?)

Edsger Dijkstra: "Computer science is no more about computers than astronomy is about telescopes."

Hint (early ‘computer scientist’ names): turingineer, turologist, flow-charts-man, applied meta-mathematician, comptologist, datalogist, computics specialist, informatik specialist

Page 3: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

3

Computer Science

• “the study of information and computation, and their implementation and application in computer systems“

[collective wisdom of Wikipedia]

• sub-areas emphasize:

– the computation of specific results (e.g., computer graphics)

– properties of computational problems (e.g., computational complexity theory)

– the challenges in implementing computations (e.g.,

programming language theory, human-computer interaction)

• in a nutshell, the study of computation

Page 4: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

4

The Study of Computation

“Computer Science is a science of abstraction - creating the right model for a problem and devising the appropriate mechanizable techniques to solve it.”

A. Aho and J. Ullman, 1992

“Computer Scientists are engineers of abstract objects”

H. Zemanek, 1975

“The two A-s of computation:

• abstraction (i.e., modeling)

- e.g., 115 pebbles the natural number 115 -> the string (array) of characters ‘115’ or ‘CXV’

• automation (mechanizing the abstraction)

Computing is the automation of abstractions.”

J. Wing, 2008

Director CISE at NSF

Page 5: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

5

Examples

• MySpace, You Tube are social networks

• DNA sequences are strings (that can be matched)

• Cells as a self-regulatory system are like electronic circuits

• Astronomy multi-dimensional data are KD-trees

Abstraction: graph

Automation: data structures and algorithms

stack queue tree (upside-down)

Page 6: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

6

Abstraction and AutomationNote: Neither abstraction nor automation are unique to Computer Science

E.g. abstractions in other fields:

Schroedinger’s equation in physics, chemistry;

natural numbers, sets & tables in math etc.

E.g. automation in other fields:

algorithms for long division or factoring in math

automated processes in engineering

(not surprising! Cca 1960: math + electrical engineering -> CS)

But implementing the “automation of abstractions” process as well as studying the properties of this process are traits of computer science.

Page 7: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

7

Computer Graphics

• Computer graphics generally means creation, storage and manipulation of geometrical models and their images

• Such models come from diverse, often non-CS fields including physical, mathematical, artistic, biological, and even conceptual (abstract) structures

Frame from animation by William Latham, shown at SIGGRAPH 1992. Latham uses rules that govern patterns of natural forms to create his artwork.

Page 8: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

8

Keyframing smoke

Adrien Treuille (UW)

Page 9: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

9

Page 10: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

10

Simulating the air flow around a bat wing

M. Kostandov (Brown)

Page 11: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

11

• Donald Burke, Pitt Public Health

Page 12: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

12

Pitt Visualization Research Lab

Page 13: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

13

Interdisciplinary Visualization

ObserveHypothesize(across disciplines)

Visualize Validate Evaluate Explore (across disciplines)

Measure Model Simulate

Insight

[Laidlaw 2005]

Page 14: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

14

Example projects

• Motion tracking

• Predictive orthopaedics modeling

• The Chinese Room: collaborative machine translation

Page 15: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

15

Motion tracking

Joint work with Yinglin Sun, MD. Abedul Haque, Scott Tashman, Bill Anderst

Page 16: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

16

(not too many sample poses – radiation concerns)

Page 17: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

17

UPMC: Orthopaedic Biodynamics Laboratory

A consecutive sequence of 2-D radiographs

Page 18: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

18 18

Tracking motion: problem imaging artifacts -> limited tracking accuracy -> bone collisions

2

2

1

1 3 4

3

4

Grey-value matching

Page 19: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

19 19

Tracking motion: solution(Marai et al.,TMI'06)

Step 1: extract bone outline from one volume image

Step 2: use tissue-classification (neighborhood) to emphasize the bone boundary

Page 20: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

20

Page 21: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

21 21

Tracking motion:solutionStep 3: optimize outline position & orientation until it matches the tissue-classified image

(illustrated here in 2D)

∑ −=

n

iTivtIivjTsI

j1

2

)()(min

Page 22: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

22 22

Tracking motion: results

grey-value tissue-classif.vs.

collisionno collision

43% error-decrease compared to grey-value matching

Results on marked cadaver data (motion error relative to ground truth, 0 is good)

Page 23: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

23 23

Tracking motion: summary● sub-voxel accurate method for tracking bone-motion

from sequences of CT scans ● 43% error-decrease from state-of-the-art technique● 12 volume images in 1.5 hours on 40 processor cluster● enables the analysis of soft-tissue deformation with

motion● results in a wrist motion database of unprecedented

detail

Page 24: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

24

Inverse-imaging biological structures

Joint work with David Laidlaw, Trey Crisco

Page 25: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

25

Computational modeling: joint-spacing and cartilage

Idea: cartilage correlates with bone proximity

parameter: p the proximity threshold

Page 26: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

26

Cartilage maps: results

Page 27: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

27

1.05mm1.21mmMax

0.276mm0.275mmMin

0.596mm ± 0.20mm0.601mm ± 0.21mmMean±Std.dev.

Non-invasively (kinem.-generated)

Invasively (µCT-imaged)

Cartilage thickness

Page 28: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

28

Predictive orthopaedic systems

Joint work with David Laidlaw, Trey Crisco, Douglas Moore

Page 29: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

29

1

2images

bone surfaces & motion

anatomy book knowledge

3

soft tissuegeometry & behavior

visualization & quantification+…

Page 30: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

30

The push-up debate (Alexis vs. Crystal)

• on your knuckles or not?

Page 31: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

31

The push-up debate (Crystal wins)

• previously: computationally intractable• CT volume images of one individual• 7 different poses (knuckle-pose included)• computed cartilage contact & ligament lengthening in

each pose• ~48 hrs, single processor• knuckle pose yields maximum contact

Page 32: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

32

The push-up debate: knuckle-walkers

Page 33: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

33

DRUJ malunion

Distal radioulnar joint (DRUJ)

Page 34: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

34

DRUJ malunion

Page 35: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

35

The Chinese Room

Joint work with Josh Albrecht & Rebecca Hwa

Page 36: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

36

What does this say?

Machine translations:

• “He utter eyes and not the slightest attention As leakage.”

• “He Zhengzhao eyes, eyes can no leakage.”

Page 37: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

37

A collaborative approach

Page 38: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

38

Chinese Room: results

Example:

• MT: “He utter eyes and not the slightest attention As leakage.”

• Chinese Room MT: “His eyes were placed wide-apart; nothing escaped their attention.”

• MT-quality improved on average from 0.35 to 0.53

• the gap between MT and pro bilingual translations reduced by 36.9%

Page 39: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

39

CS 2620Interdisciplinary Modeling and Visualization

• Pitt CS Teaching Award ’08

• offered Spring’09

• Mon/Wed 11am

• visualization nuts and bolts

• 2nd half: work in small multidisciplinary groups

Image credits: cs2620 alumni J.Albrecht, M.Grabmair, Yl.Sun, J.D.Park, M.Fagerburg

Page 40: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

40

Contact

• http://vis.cs.pitt.edu

[email protected]

• SENSQ 5423

Page 41: Liz Marai 01/30/09 1 Computational Modeling and Visualization for Science Liz Marai Computer Science

Liz Marai 01/30/09

41