BIOPHYS 430 001 WN 2025
Instructor: Magdalena Ivanova Email mivanova@umich.edu
Class Schedule M/W 8:30 am-10:00 am RM3230 USB
Office hours Zoom https://zoom.us/my/amyloid PWD 430440 11AM-12PM Wed
Class Calendar Refer to for information on class topics, guest lectures, homework, and assignment due dates.
Maizey An AI tutor trained specifically on the class materials.
Course Description
The course will cover a range of imaging techniques used in modern medicine, including ultrasound, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). Each of these techniques will be studied in terms of the underlying physical principles that make them effective tools for diagnosing and monitoring medical conditions. For example, ultrasound relies on the reflection of sound waves, CT uses X-rays to acquire detailed cross-sectional images, MRI uses the magnetic properties of atoms for imaging, and PET utilizes radioactive tracers to detect metabolic processes.
Additionally, radiotherapy methods that use high-energy radiation to treat cancer will be covered. Students will learn about the physical basis of this technique, including the interaction of radiation with biological tissues, treatment planning, and safety considerations.
The course will also introduce the physics of physiological processes such as muscle contraction, cardiovascular dynamics, neuronal signaling, and renal filtration. These systems will be examined through the lens of physics, using models to describe their behavior and aid in diagnosing diseases.
Guest lectures from leading experts in the field will provide students with real-world perspectives on current innovations and challenges in biomedical imaging and therapy. These sessions will offer a unique opportunity to learn from the best and provide a deep dive into cutting-edge research and the latest technological developments.
Assignments in the course will be designed to help students apply their knowledge to practical problems, with a focus on data analysis and project-based learning. You will gain hands-on experience using R-Studio, a powerful platform for data analysis, which will be used for processing imaging data and interpreting results from various biomedical physics applications.
Materials and resources
Intermediate Physics for Medicine and Biology, by Hobbie & Roth
Physics in Biology and Medicine, by Paul Davidovits
Guide to Research Techniques in Neuroscience, by Carter & Shieh
Biomedical physics with applications to disease, by Ivanova & Dinov
R and Rmarkdown orientation, by Dinov
Lecture availability Lectures will be recorded via Zoom and posted on Canvas under Pages. You can also download the lectures in PDF format from Canvas under Files > Lectures.
Accommodations for Students with Disabilities
If you need accommodation for a disability, please let me know at your earliest convenience. Your information is private and confidential and will be treated as such.
Religious holidays and other time conflicts
Please let me know during the first two weeks of the semester if you have conflicts with the listed examination dates.
Grading
Grades will be based on a midterm exam (20%), 4 homework assignments (take home 40%), attendance (5%), in-class paper presentation (15%), and a final project (take home - 20%).
Late submission OR Illegible writing will incur a penalty of up to 20%.
Attendance
Attendance will be taken for the guest lectures and in-class presentations. You may miss one lecture and still receive full attendance credit.
If you are unable to attend in person due to illness, personal matters, or professional commitments, please email me ahead of time.
In-class paper presentations
For this assignment, students will be teamed in groups, and all group members should be present in person. Please plan accordingly to attend. If you cannot attend due to sickness, please let your group member(s) AND the instructor know as soon as possible. Group members will share the same grade.
Grades will be assigned using standard tables.
|
Grade |
Range |
|
|
A |
100 % |
to 93.0% |
|
A- |
< 93.0 % |
to 90.0% |
|
B+ |
< 90.0 % |
to 87.0% |
|
B |
< 87.0 % |
to 83.0% |
|
B- |
< 83.0 % |
to 80.0% |
|
C+ |
< 80.0 % |
to 77.0% |
|
C |
< 77.0 % |
to 74.0% |
|
C- |
< 74.0 % |
to 70.0% |
|
D+ |
< 70.0 % |
to 67.0% |
|
D |
< 67.0 % |
to 64.0% |
|
D- |
< 64.0 % |
to 61.0% |
|
F |
< 61.0 % |
to 0.0% |
Course Summary:
| Date | Details | Due |
|---|---|---|
This course content is offered under a CC Attribution Share Alike license. Content in this course can be considered under this license unless otherwise noted.