CSE 554: Geometric Computing for Biomedicine

1. CSE 554: Geometric Computing for Biomedicine Fall 2013

2. Outline • Introduction to course • Mechanics • Mathematica demo

3. Outline • Introduction to course • Mechanics • Mathematica demo

4. Geometry • Greek word: Earth-measuring • One of the oldest sciences Chinese Chou Pei Suan Ching (500-200 BC) Euclid’s Element (300 BC)

5. Geometry • Greek word: Earth-measuring • One of the oldest sciences Newton’s Principia Mathematica (1687) Einstein’s General Relativity (1915)

6. Geometric Computing • Algorithms and data structures for manipulating geometric forms

7. Geometric Forms Curves Surfaces • Continuous forms • Defined by mathematical functions • E.g.: parabolas, splines, subdivision surfaces • Discrete forms • Disjoint elements with connectivity relations • E.g.: polylines, triangle surfaces, pixels and voxels Polyline Triangle surfaces (meshes) Pixels Voxels

8. Geometric Computing • Algorithms and data structures for manipulating (discrete) geometric forms • Creation • From 2D/3D images, from point clouds, by hand, etc. • Processing • De-noise, simplify, repair, transform, animate, etc. • Analysis • Geometric, topological, shape and physical properties

9. Applications Industrial design Cultural heritage Engineering simulation Geology Movie CG

10. Application: Biomedicine • Modeling biological structures as geometric forms • A spectrum of scales: organs, tissues, cells, molecules, etc. • Utility of geometric models • Visualization • Quantitative analysis • Simulation and interaction Human Virus Treatment planning Surgical simulation

11. This Course • Classical algorithms for geometric computing • Those that have been useful for biomedical image analysis • Easy to understand, simple to implement

12. This Course • Working with biomedical imaging data • 2D: Light microscopy, slices of 3D images • 3D: Magnetic resonance imaging (MRI), Computed tomography (CT), Cryo-Electron Microscopy (Cryo-EM) Microscopy Cryo-EM CT

13. This Course • Creating, processing, deforming, and analyzing geometry Fair & Simplify Segment Contour Shape analysis Align (Before) (After)

14. Beyond This Course • On-going research projects on biomedical modeling • Gorgon: protein modeling tool for density volumes (Gorgon.wustl.edu) • Geneatlas: atlas-based gene expression pattern exploration (Geneatlas.org) • VolumeViewer: interactive 3D segmentation tool (Volumeviewer.cse.wustl.edu) • Research opportunities in the M&M lab • Biomedical modeling (Tao) • Image analysis (Robert, Tao) • Computer vision (Robert, Yasu) • Machine learning (Kilian) • Human computer interaction (Caitlin)

15. Outline • Introduction to course • Mechanics • Mathematica demo

16. Staff • Instructor: Tao Ju • Jolley 406 (taoju@cse.wustl.edu) • TA: • Ming Zou (mingzou.cn@gmail.com) • Derek Burrows (derek.wayne.burrows@gmail.com)

17. Prerequisites • Programming • Experienced in at least one of the major programming languages • C/C++, Java, Matlab, Python, etc. • CSE332 is strongly recommended • CS background • Basic data structures (e.g., queues, trees, hash tables) and algorithms • CSE241 is strongly recommended • Math • Linear algebra, elementary geometry

18. Overview • 2 meetings per week • Lectures on Tuesdays (Lopata 229) • Lab working (with instructor and TA) on Thursdays (Whitaker 130) • 5+1 lab modules • 2 weeks for each module (1 week for Module 0) • Due and graded in lab on Thursdays. • 1 course project • Start in October • Due end of semester • Check out the calendar on course webpage No exams!

19. Lectures • Theory and algorithms • Power-point slides available before each lecture on the webpage • Algorithms are explained in depth, pseudo-code given when possible Example: • … • Repeat until Q is empty: • Pop a pixel x from Q. • For each unvisited object pixel y connected to x, add y to S, set its flag to be visited, and push y to Q. • Output S

20. Lab Modules • Algorithm prototyping (in Mathematica) • Modules designed to help you implement the algorithm step-by-step • Emphasis on unit testing • Work individually Example:

21. Course Project • A working tool for bio-medical data analysis • Addressing problems in on-going bio-medical research • Meet the need of the specific research problem to a sufficient extent Measuring small bowel length (by Billy Bennett) Breast lesion segmentation (by Noa Ben-Zvi)

22. Course Project • Use your favorite programming language • Work in team or individually • Schedule: • October 8: Instructor presents candidate project ideas • October 24: Project proposals are due • December 3/5: In-class project demos

23. Grading • Lab modules: 75% (graded during Thursday lab time) • Course project: 25% • Late policy • Late modules and project will earn at most 50% credit for the late part • Modules submitted later than the Tuesday following the due date will not be accepted. • Extensions will be given only under exceptional conditions, by written requests ahead of time.

24. Outline • Introduction to course • Mechanics • Mathematica demo

25. Action Items – This Week • Make sure you have a SEAS account • Check with the help desk at EIT in Lopata 4nd floor. • Get access to Mathematica • Available on all SEAS machines, and can be installed freely on campus • Purchase for personal use for $45 / semester • Module 0 is out today • I will give a quick tutorial and help you with it this Thursday • Due and graded next Thursday in lab (Sept. 5) • See you all on Thursday (Whitaker 130)!