Radiography Image Analysis Assignments

Methods In (Bio)Medical Image Analysis - Spring 2018

16-725 (CMU RI) : BioE 2630 (Pitt)

(Frequently also crosslisted as 18-791, CMU ECE : 42-735, CMU BME)


John Galeotti


Usually meets with students after class


Peiyun Hu


By email or appointment

Syllabus (general)

Meeting in NSH 1305
(at Carnegie Mellon University, see campus map)

Class begins Tuesday, Jan. 16th!
Class ends Thursday, April 26th.

Lecture Times and Locations

We comply with both the U. Pitt. and CMU calendars. Lectures are Tuesday and Thursday from 10:30-11:45 AM, in NSH 1305, Carnegie Mellon University.

Shadow Program Times, Locations, & Details

Shadow Program:  6 radiology sessions and 0-2 (TBD) pathology sessions, 8:30-9:30 AM weekday mornings (and possibly other times optional for shadowing pathology).

Online schedule, directions, and required UPMC confidentiality agreement. Reports should be emailed to your TA and Galeotti.

Textbooks, Downloads, & Other References

Last Year's Website has been archived.

Key ITK Documentation:

Assignments (please do not start until assigned in the schedule)

Assignment #1 - Introductory Email

Assignment #2 - Get ITK & SimpleITK installed, etc.

Assignment #3 - iPython Notebooks: Segmentation by Thresholding #1

Assignment #4 - Use SimpleITK to do Segmentation and Pre-processing

Assignment #5 - Registration (optional)

Final Project

Schedule—Subject to Change
(Future plans are tentative, based on the old 2017 schedule)

Note about videos: Lecture videos were recorded in 2012, and you can downlaod the lecture videos from the 2012 schedule here. Be sure to download the videos (right-click the video's link then select either "download" or "save-as") rather than try to watch them in your browser. Please let me know if you notice any problems or video content that should be either fixed or trimmed out if it's not relevant to a general audiance (please reference the 2012 lecture number and the playing time into the video at which the problem occurs).

Week #DateUpdated for 2018?MaterialVideo and .pptx files

Week 1

Tu 1/16


Lecture 1: Introductions, purpose, Syllabus

Power Point
Video (from 2012)

Lecture 2: Programming background:  C++ & Python
Assignment #1 given

WARNING: Quiz on book reading next class!

Power Point
Video (from 2012)

Week 2

Tu 1/23


To prepare for the quiz, I suggest focussing on big-picture concepts and major themes, what algorithms/methods are trying to do, what they are good for, and (if the text goes over it) when/how they typically fail.

Lecture 3: Math & probability background
Begin class with a short QUIZ on Snyder ch. 1-2
Finish programming background (starting with typedef)

Power Point
Video (from 2012)

Th 1/25


Lecture 4: ITK background & basic usage
CMU's add/drop-with-refund period ends sometime around now.

Power Point
Video (from 2012)

Week 3

Tu 1/30


Lecture 5: Image characterization
Quiz #2 on Snyder ch. 4 (skip hexagonal coordinates on pp 57-59)

Assignment #2 given.

Power Point
Video (from 2012)

Th 2/1


Lecture 6: Linear processing
Quiz #3 on Snyder 5.1-5.6,5.8-5A (through page 101, but skip hexagonal coordinates on pp 71-73 and skip 5.7)

Power Point
Video (from 2012)

Week 4

Tu 2/6


Finish Linear processing (resume Scale Space at slide 15)
Lecture 7: Image relaxation: restoration & feature extraction
Quiz #4 on Snyder ch. 6
HW2 due 5pm Wednesday the 7th.

Power Point
Video (from 2012)

Th 2/8


Lecture 8: ITK registration

Power Point
Video (from 2012)

Week 5

Tu 2/13


Finish Image relaxation (resume Minimization at slide 18)
Lecture 9: Segmentation, part 1
Quiz #5 (the most in-depth quiz of the class) on Snyder ch. 8 (skip 8.3.2 on pp. 189-196 & 8A.1.1 on pp. 208-209)

Power Point
Video (from 2012)

Th 2/15


Lecture 10: Segmentation, part 1 continued (using previous notes, start with slide 5)

HW3 may be posted later today.



Week 6

Tu 2/20


Lecture 11: Segmentation, part 3 (active contours)

Assignment #3 is now assigned, due 5pm Thursday (2 day extension)

Power Point
Video (from 2012)

Th 2/22


Follow Up: HW3—easy/helpful? Issues with web browsers, snap, or PDF?

Discuss Shadow Program & signup procedure in class (normal time, 10:30am)

Imaging Modalities mini-lecture; finish PDE active contours

Shadow Program — be sure to sign up for the Shadow Program THIS WEEK, beginning at 3:15 pm Sunday (link is here; you may be able to sign up for stations faster if you create an account on in advance).

Shadow Program Power Point

Imaging Modalities Power Point(contains embedded movies)
Video (from 2012, skip to end for imaging modalities)


Week 7

Tu 2/27


Shadow Program starts TODAY--show up on your days at 8 am (with UPMC form!) until you know where you're going
How is the shadow program going?

Follow Up: HW3—easy/helpful? MS Edge & PDF? Shadow? 2-day extension
Plan: Spring Break & NeuroPath

Discuss final projects
Be sure to email me your initial project idea / tentative proposal by the night of Thursday the 15th.
Go over example projects.

Finish Lecture 11.
Lecture 12: Level set segmentations & (briefly begin) parametric transforms (Snyder 8.5.2 & Snyder 11.1-11.6) [not required, but recommended: Insight into Images ch 8]
Quiz on Snyder 11.1-11.6

Final Project Power Point

Power Point
Video (from 2012)

Th 3/1


Finish Lecture 12: Level set segmentations & parametric transforms

HW3 revised due date 5pm today

Segmentation Assignment (ready now) assigned Monday March 5th, due 10pm Wednesday the 21st. SVN accounts have been distributed. If you didn't yet receive your svn account by email, let you instructor know.



Pitt Spring Break

3/6 - 3/8


No In-Class Lectures: Instead, there are two lectures below for which you should watch the videos.

Due to non-overlapping spring breaks this year, you should expect some type of online/take-home assignment that you can do during the time of your choosing during this 2 weeks.

Revised Project proposals will be readily accepted through Thursday night the 30th.


CMU Spring Break

3/13 - 3/15

S.B. #1

Lecture SpringBreak1: ITK images & iterators

Power Point
Video (from 2012)
  S.B. #2Lecture SpringBreak2: ITK pipeline, including reading/writing images and connecting to SimpleITKPower Point
Video (from 2012—link fixed March 14th)

Week 8

Tu 3/20


Special 8:30am group shadow: NeuroPathology

Lecture 12 Registration in depth (Insight into Images ch 10 + Viola & Wells)

Segmentation assignment due 10pm tomorrow!

Power Point
Video (from 2012)

Th 3/22


Lecture 13: Shape
Quiz on Snyder ch. 9 (read 9.1-9.8, 9.12-9.14)

Lecture 14: Summarize Cootes and Taylor ASM (Cootes CVIU 1995)

Power Point
Video (from 2012)

Power Point (public version)


Week 9

Tu 3/27


Lecture 15: ITK filters: how to write them (neighborhoods, image boundaries, & numeric traits)

Power Point
Video (from 2012)

Th 3/29


Lecture 16 Mathematical morphology & image matching
Quiz on Snyder 7.1-7.5 & 13.1-13.5

Revised project proposals due tonight

Power Point
Video (from 2012)

Week 10

Tu 4/3


Lecture 17: ITK filters, part 2 (advanced filter creation & useful ITK filters you should know about)
CMU's drop-without-withdrawl period ends today

Power Point
Video (from 2012)

Th 4/5


Lecture 18 Deformable registration (Insight into Images ch 11)

Special NeuroPath Shadow Monday 8:30: Enter Scaife Hall from the main doors on Terrace street (directly across from the Peterson event center). Take an elevator up to the 7th floor, then go right as you exit the elevator and go through a set of double doors.

Homework deadline extended (numerous student questions during my travel), now due: Friday April 7, 5pm.

Power Point
Video (from 2012)
  Note: CMU's drop-without-withdrawl period ends on March 30th (Monday) 

Week 11

Tu 4/10


Special Help Session for Final Projecrts: after working on your project over the weekend, bring your questions to this special "office hours" help session, same time and place as normal lecture.

Special note about Neuropathology bonus points (max 2 points per person):

  • If you showed up to neuropath 8:30am yesterday, you can turn in a normal shadow report for +2 bonus points on your final grade.
  • If you didn't or weren't able to show up, you can insead write a 2-page short research report (same topics as a showdow report) covering your own research into neuropathology, to get the same 2 bonus points.


Th 4/12


Summarize Final Project Expectations, new TA reminder
Answer student questions
Lecture 19: ITK Paths
Presentation order to be assigned over weekend--email (only hard) conflicts today!

Power Point
Video (from 2012)


Week 12

Tu 4/17


Student project presentations (see random order email)
(Each presentation must be ~8 minutes long.)
Everyone's slides due in svn by 10 AM today! (.pptx format preferred, or else .ppt or .pdf)

Th 4/19

 No Lecture - CMU Spring Carnival 

Week 13

Tu 4/24


Student project presentations (presentation order)


Th 4/26

 Student project presentations & Projects Due 

Special Topics CAP5937-Medical Image Computing (SPRING 2016)

Assistant Professor  •  Imaging Scientist  •   •  Home  •  Courses  •  CRCV  •  Research Blog  •  Publications  • 

Instructor: Prof. Ulas Bagci    

Class time: Monday/Wednesday 10.30-11.45 am
Class location: HPA1 0106
Office hours: Monday/Wednesday 3-5 pm

COURSE GOALS: Imaging science is experiencing tremendous growth in the US. The New York Times recently ranked biomedical jobs as the number one fastest growing career field in the nation and listed bio-medical imaging as a primary reason for the growth. Biomedical imaging and its analysis are fundamental to understanding, visualizing, and quantifying medical images in clinical applications. With the help of automated and quantitative image analysis techniques, disease diagnosis will be easier/faster and more accurate, and leading to significant development in medicine in general. The goal of this course is to help students develop skills in computational radiology, radiological image analysis, and biomedical image processing fields. The following topics will be covered:
  • Basics of Radiological Image Modalities and their clinical use
  • Introduction to Medical Image Computing and Toolkits
  • Image Filtering, Enhancement, Noise Reduction, and Signal Processing
  • Medical Image Registration
  • Medical Image Segmentation
  • Medical Image Visualization
  • Machine Learning in Medical Imaging
  • Shape Modeling/Analysis of Medical Images
PRE-REQUEST: Basic Probability/Statistics, a good working knowledge of any programming language (python, matlab, C/C++, or Java), Linear algebra, Vector calculus.

GRADING:Assignments and mini projects should include explanatory/clear comments as well as a short report describing the approach, detailed analysis, and discussion/conclusion.
  • Programming assignments 30% (3 assignments, 10% each)
  • Midterm 20%
  • Project 50% (Presentation: 15%, Software/methods/results: 35%)
  • Suetens, P. Fundamentals of Medical Imaging, Cambridge University Press
  • Prince, J. & Links, J. Medical Imaging Signals and Systems, Prentice Hall,
  • Bankman, Isaac.Handbook of Medical Imaging: Processing and Analysis, Academic Press,
  • Yoo, Terry S. Insight into Images: Principles and Practice for Segmentation, Registration and Image Analysis, CRC Press,
  • Sethian, J.A., Level-set Methods, Cambridge University Press, 2000,
  • Duda, Hart and Stork, Pattern Classification (2nd Edition), Wiley, 2000,
  • Koller and Friedman, Probabilistic Graphical Models: Principles and Techniques, MIT Press, 2009,
  • Strang, Gilbert. Linear Algebra and Its Applications 2/e, Academic Press, 1980.
Students are enocouraged to use ITK/VTK programming libraries in implementation of the programming assignments and project.
ITK is an open-source, cross-platform system that provides developers with an extensive suite of software tools for image analysis.
The Visualization Toolkit (VTK) is an open-source, freely available software system for 3D computer graphics, image processing, and visualization. It consists of a C++ class library and several interpreted interface layers including Tcl/Tk, Java, and Python.

Python and/or C/C++ can call functions of ITK/VTK easily. Matlab can be used for assignments as well.
Following book (Python programming samples for computer viion tasks) is freely available.
Python for Computer Vision

Collaboration on assignments is encouraged at the level of sharing ideas and technical conversation only. Please write your own code. Students are expected to abide by UCF Golden Rule.




  • Lung Lobe Segmentation from CT Scans (Use LOLA11 Segmentation Challenge Data Set)
  • Segmentation of Knee Images from MRI (Use SKI 2010 Data Set))
  • Multimodal Brain Tumor Segmentation (Use BraTS Data Set)
  • Automatic Lung Nodule (cancer) Detection (Use LUNA Data Set)
  • Automatically measure end-systolic and end-diastolic volumes in cardiac MRIs. (Use Kaggle Cardiac Data Set)
  • Head-Neck Auto Segmentation Challenge (Use MICCAI 2015 Segmentation Challange Data Set)
  • CAD of Dementia from Structural MRI (Use MICCAI 2014 Segmentation Challenge Data Set)
  • DTI Tractography Challenge (Use MICCAI 2014 Segmentation Challenge Data Set)
  • EMPIRE 2010 - Pulmonary Image Registration Challenge (, I have the team name and password for downloading the data set).
  • Digital Mammography DREAM challenge < LINK>
  • MACHINE LEARNING Challenge in medical imaging < LINK>)


will be updated soon...


Name: UlasBagci
Work number: (+1) 407-823-1047
Fax number: (+1) 407-823-0594
CRCV Assistant: Tonya
Mailing address: Dr. Ulas Bagci
Center for Research in Computer Vision (CRCV)
4328 Scorpius Street, HEC 221, UCF
Orlando, Florida32816, USA.

Last updated September, 2015 by Ulas Bagci.

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