CSC 621-821: Biomedical Imaging & Analysis
Fall 2023 (#10228, #10229)
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Instructor: Dr. Kazunori Okada |
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Lecture Time |
Tue: 4:00 - 6:45 pm |
Location |
Thornton Hall 329 |
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Office Phone |
(415) 338-7687 |
Office Location |
Online (see iLearn) |
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Office Fax |
(415) 338-6826 |
Office Hours |
Thr: 3:30 - 4:30 pm |
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Email Address |
Web Page |
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Mailing Address |
Computer Science Department, San Francisco State
University |
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Teaching Assistant |
Chris Huber |
TA Office Hour TA Office |
Ad-hoc Discord (see Canvas) |
Course Web Page: https://bidal.sfsu.edu/~kazokada/csc621-821/
Course Summary:
This course, an introduction to biomedical imaging and analysis, covers two main components: physical image formation (e.g., imaging physics, 3D imaging, image formats, visualization) and computational data analysis (e.g., digital image processing, filtering, registration, segmentation, quantification). The objectives of this course include developing comprehensive overview of basic topics in biomedical imaging & analysis and deeper knowledge of a specific biomedical imaging and analysis application. This is a paired course. CSC621 is for upper-division undergraduates while CSC821 caters to graduate students with additional assignments.
Prerequisites: CSC621: Upper-division standing; CSC510 and MATH 325 with grades of C or better; GPA of 3.0 or higher; or consent of the instructor. CSC821: Graduate standing or consent of the instructor.
Textbooks:
[t1]: Digital Image Processing (4th, Ed), R.C. Gonzalez and R.E. Woods. Prentice Hall, 2018 (3rd edition is also fine: optional for 621) https://www.pearson.com/us/higher-education/program/Gonzalez-Digital-Image-Processing-4th-Edition/PGM241219.html
[t2]: Fundamentals of Medical Imaging (3rd Ed), P. Suetens, Cambridge University Press, 2017 (2nd edition is also fine: optional for 621 & 821) https://www.cambridge.org/us/academic/subjects/medicine/medical-imaging/fundamentals-medical-imaging-3rd-edition?format=HB&isbn=9781107159785
[t3]: Introduction to Biomedical Imaging (2nd Ed), A. Webb, Wiley, 2022 (optional for 621 & 821) https://www.wiley.com/en-gb/Introduction+to+Biomedical+Imaging,+2nd+Edition-p-9781119867715
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Lecture Plan (subject to change) |
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Week |
Topic: Lecture |
Notes |
Readers |
Assignments |
Exam |
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01:08/22 |
Course Overview: Framework, History, Applications |
[t1] Ch1 [t2] Ch1-2 |
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02:08/29 |
Imaging Methods & Physics: Optical, X-ray, CT, MRI |
[t2]Ch2-6 [t3] |
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03:09/05 |
Imaging Methods & Physics: PET, US, Fusion, Biology |
[t2] Ch2-6 [t3] |
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04:09/12 |
Image Data Structure Image Visualization |
[t2] Ch8 |
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05:09/19 |
Digital Image Processing: Practical Foundation |
[t1] Ch2-3 |
Due: project design |
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06:09/26 |
Digital Image Filtering: Spatial Domain |
[t1] Ch3 |
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Midterm 1 |
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07:10/03 |
Digital Image Filtering: Frequency Domain |
[t1] Ch4 |
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08:10/10 |
Advanced Processing: Edge Detection & Morphology |
[t1] Ch9-10 |
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09:10/17 |
Image Segmentation: Thresholding, Region Growing |
[t1] Ch10 |
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10:10/24 |
Image Segmentation: Watersheds, Level Sets, Graph |
[t1] Ch10 |
Midterm 2 |
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11:10/31 |
Image Registration: Geometry-based Registration |
[t2] Ch7 |
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12:11/07 |
Image Registration: Intensity-Based Registration |
[t2] Ch7 |
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13:11/14 |
Image Quantification: Change Analysis, Classification |
[t1] Ch11-12 |
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14:11/21 |
Thanksgiving Recess |
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15:11/28 |
Group Project Work Day |
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Due on 12/04 5pm: Presen files |
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16:12/05 |
Project Final Presentation |
Due on 12/08 10pm: Final-&-LS Reports |
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Important Dates:
09/26: Midterm 1
10/24: Midterm 2
12/04: Due (5pm via email): Files needed for final presentations.
12/08: Due (10pm via email): Final Project Report
12/08: Due (10pm via email): Literature Survey Report (Only 821)
12/12: Final Exam Slot from 5:00pm – 6:45pm
09/11: Last day to add; Last day to drop without W grade.
Office Hours:
Office hours will be available for online conversations with both the instructor and the TA during the time specified above. Zoom links for them will be available on the Canvas course page. Students are requested to make yourself visible by turning the video on. Students will be met on a first-come first-served basis. Please email the instructors ahead of time to reserve a specific time slot of 10-20 minutes, should you have important issues to consult with.
Canvas Usage:
Canvas will be used to share general information of this course, links to discussion forums, as well as resources for the final projects. Zoom links to the office hours of the instructors as well as the TA will also be shared on Canvas.
Final Project: Developing a Biomedical Image Analysis System
Students will engage in a hands-on group project for developing a biomedical image analysis system using public APIs. This year we will target building and experimenting a system that analyzes chest CT scans of Covid-19 patients. Each group will consist of about 5-6 students including graduate or advanced students who may act as team leads who mentor other undergraduate members. With data provided, each group will identify, design, implement and evaluate specific data analysis algorithms. For coding platform, students will use Insight Segmentation and Registration Toolkit (ITK: http://www.itk.org/) with C++ or (SimpleITK: https://simpleitk.org/TUTORIAL) with Python. Students will then present their resulting work, as a group, at the end of semester while each student is required to submit a final report written individually. Student’s work will be graded based on the quality and completeness of these individual report and group presentation. Late policy will apply. Please read the assignment carefully for more details.
Literature Survey Report (Only 821):
An independent literature survey study is to be carried out by each graduate student taking CS821 in order to help them learning how to write their own thesis. Students must i) choose a subtopic related to biomedical imaging & analysis research, ii) conduct a survey of the subtopic’s recent literatures consisting of minimum of five representative peer-reviewed published articles, and iii) submit a written report summarizing and critiquing the survey results. The report must follow the SFSU thesis format specified in the university guidelines and should be around 18 double-spaced pages (two-page introduction, two pages for each paper, four page critique and conclusion, and two page reference list). Late policy will apply. Please read the assignment carefully for more details.
Exams:
There will be two midterms. No final exam.
Quiz/Homework:
No quiz and homework is currently planned. There may be some quizzes with a short notice for making sure that you are following the covered materials.
Numerical Grade Weights for 621 (for 821):
· 60% (40%): Midterms
· 40% (40%): Final Project
· 0% (20%): Literature Survey Report
· In general, students will be evaluated on their ability to devise, organize and present complete solutions to problems. Solutions need to be presented in a neat and organized way; cryptic answers or untidy presentation will not be graded. Completing answers to all problems with sound and in-depth analytical reasoning are required; a correct answer with no reasoning or with wrong reasoning will result in no (partial) credit
· The grade distribution is as follows: A (100% - 92.5%), A- (92.4%-90%), B+ (89.9% - 87.5%), B (87.4% - 82.5%), B- (82.4% - 80%), C+ (79.9% - 75%), C (74.9% - 65%), C- (64.9% - 60%), D+ (59.9% - 57.5%), D (57.4% - 52.5%), D- (52.4% - 50%), F (49.9% - 0%).
Late Policy:
· No make-up exams and homework late submission will be allowed. If you know that you will be missing an exam or assignment due, you must notify the instructor as soon as possible.
· When allowed, late submission will be penalized by 10% per day up to 50%.
· After 5 days, late assignments receive zero credit.
Grade Appeal:
To appeal your grades on assignments and exams, you must do so within one week after graded assignments/exams were returned or made available to students. There will be no exception even if you miss those classes and/or announcements. You are responsible to find out your own grades.
Absence:
Regular attendance is recommended as attending lectures is the best way to learn the material. From the SFSU bulletin: “Students are expected to attend classes regularly because classroom work is one of the necessary and important means of learning and of attaining the educational objectives of the institution.” In the event of an absence, it is the student’s responsibility to learn of any material missed and acquire assignments and announcements given during the class. Lectures and demonstrations will not be repeated during office hours. In case of extraordinary circumstance, it is the student’s responsibility to inform the instructor and submit supporting documents as soon as s/he can.
Syllabus is Subject to Change:
This syllabus and schedule are subject to change. The official syllabus will be maintained at the course website. It is your responsibility to check on the site frequently and even when revisions are made while you are absent.
Academic Integrity & Plagiarism:
Academic integrity, the ethical presentation of one's own work in accordance with the rules established for this class, is required. Instances of academic misconduct will be reported to the College in which the course is housed, the Division of Graduate Studies (if a graduate student), and the Office of Student Conduct with the report being kept in those offices until a student earns his/her degree. Any instances of cheating, deceit, fabrication, forgery, plagiarism, unauthorized altering of records or submitting false documents, unauthorized collaboration, unauthorized submission of work previously given credit, or other forms of academic misconduct will be assigned a grade penalty, likely an F or a grade of zero. Failing one or more assignments or examinations for reasons of academic integrity violations may result in a final class grade of F. Students may not withdraw from classes in which they have committed academic misconduct. Consequences for violations of academic integrity may exceed an F on the assignment, examination, or class as determined by the Academic Integrity Review Committee.
Members of our academic community have a responsibility to develop an awareness of academic integrity, to cultivate skills to realize honesty in academic and community work, and to sustain actively academic honor as a core value of our community. Students are expected to engage in behaviors that reflect well upon the university. In addition to attending to one's own actions, the Standards for Student Conduct require that students who witness academic dishonesty notify their faculty/instructor, department chair, or the Office of Student Conduct. Supporting academic integrity enhances the reputation of the University and the value attributed to degrees awarded by the University.
I encourage discussion among students, but I expect each student to hand in their original work. You are responsible for doing your own work and for ensuring that your work is protected from copying. Usage of online cheating sites, such as a use of Chegg.com and CourseHero.com, is strictly forbidden. Violation of this rule will be treated seriously without any leniency. Your continued enrollment in this class indicates that you have carefully and entirely read and pledge to abide by the Honor Code published on the Canvas page of this course and accept the consequences to violations of its terms. Violation of the university and departmental rules (found in below links) is a serious offence and can result in severe penalties. It is your responsibility to familiarize yourself with the following rules:
· SFSU Code of Student Conduct: http://conduct.sfsu.edu/standards
· Academic Dishonesty: http://conduct.sfsu.edu/academic-dishonesty
· Plagiarism: http://conduct.sfsu.edu/plagiarism
· Computer Science Department Policy: https://cs.sfsu.edu/student-policies#accordion-collapse-accordion-824-2
Learning Assistances:
The Tutoring and Academic Support Center (TASC) is a new university-wide center that supports the academic success of all San Francisco State students. They are offering services online via Zoom. Please email tutoring@sfsu.edu from your SF State email address with your name, student ID, course for which you are seeking tutoring, and available days/times for an appointment. They will reply with details for your online appointment. More information can be found at https://tutoring.sfsu.edu/.
· Phone Number: 415-405-5516
· Location: LIB 220 (In-person) & Zoom (Online)
· Hours: Mon-Thr, 9:00 a.m. to 5:00 p.m. and Fri, 10:00 a.m. to 2:00 p.m.
· Email: tutoring@sfsu.edu
Religious Holidays:
Reasonable accommodations will be made for you to observe religious holidays when such observances require you to be absent from class activities. It is your responsibility to inform the instructor during the first two weeks of class, in writing, about such holidays.
Disability Access:
Students with disabilities who need reasonable accommodations are encouraged to contact the instructor. The Disability Programs and Resource Center (DPRC: https://access.sfsu.edu/) is available to facilitate the reasonable accommodations process. The DPRC is located in the Student Service Building and can be reached by telephone (voice/415-338-2472, video phone/415-335-7210) or by email (dprc@sfsu.edu).
Student Disclosures of Sexual Violence:
SF State fosters a campus free of sexual violence including sexual harassment, domestic violence, dating violence, stalking, and/or any form of sex or gender discrimination. If you disclose a personal experience as an SF State student, the course instructor is required to notify the Title IX Coordinator by completing the report form available at http://titleix.sfsu.edu, emailing equityprograms@sfsu.edu or calling 338-2032.
To disclose any such violence confidentially, contact:
· The SAFE Place - (415) 338-2208; http://www.sfsu.edu/~safe_plc/
· Counseling and Psychological Services Center - (415) 338-2208; http://psyservs.sfsu.edu/
· For more information on your rights and available resources: http://titleix.sfsu.edu
Kazunori Okada © 2023, All rights are reserved.