585.703.81 - Applied Medical Image Processing

Expanded Course Description

Prerequisites

585.409—Mathematical Methods for Applied Biomedical Engineering OR
535.441—Mathematical Methods for Engineers OR
A written permission from the instructor

Course Structure

The course materials are divided into modules which can be accessed by clicking Course Modules on the course menu. A module will have several sections including the overview, content, readings, discussions, and assignments. You are encouraged to preview all sections of the module before starting. Most modules run for a period of seven (7) days, exceptions are noted in the Course Outline. You should regularly check the Calendar and Announcements for assignment due dates.

Course Topics

• Medical Imaging Modalities - Computed Tomography, Ultrasound, MRI, and PET
• Medical Image Formats
• Image Enhancement
• Noise Reducing Filters - Basic, Edge-Preserving, Bilateral, Anisotropic, and Geometry Preserving Diffusion
• Image Segmentation - Automatic Binary and Minimum Error Thresholding, and Unsupervised Tissue Classification
• Image Registration

Course Goals

To identify and describe the mathematical foundations of medical image processing and then apply that knowledge to implement algorithms to perform medical image intensity enhancement, denoising, segmentation, and registration.

Course Learning Outcomes (CLOs)

• Explain physical foundation behind several medical imaging modalities (magnetic resonance (MR), computed tomography, ultrasound, and Positron emission tomography (PET).
• Explain how two and three-dimensional digital medical images are represented and stored.
• Estimate coordinates in medical images based on mathematical tools that are used to define orientation of medical image volume.
• Compose algorithms to modify intensity histograms to enhance information in images or match intensity profiles in images.
• Build computer tools to perform linear and non-linear image-based filtering.
• Build computer tools to perform semi-automatic delineation of regions of interests in medical images using segmentation techniques that rely on different features such as image intensity profile and spatial intensity change.
• Formulate algorithms to perform geometric transformation, image interpolation, similarity measures, regularizations, and optimization approaches that are used in image matching.
• Explain techniques that are used to establish correspondence between medical images.

Textbooks

None. We will be using the course lectures provided in each module.

Required Software

You will need access to a recent version of MATLAB. A license is provided at no cost to you, through JHU.

Student Coursework Requirements

It is expected that each module will take approximately 7–10 hours per week to complete. Here is an approximate breakdown: reading the assigned sections of the texts (approximately 1–2 hours per week) as well as some outside reading, listening to the audio annotated slide presentations (approximately 2–3 hours per week), and assignments (approximately 4–5 hours per week).

This course will consist of the following basic student requirements:

Preparation and Participation (15% of Final Grade Calculation)

You are responsible for carefully reading all assigned material and being prepared for discussion. Additional reading may be assigned to supplemental text readings. Grading for this requirement will work as follows: 

• Post your initial response to the discussion questions by creating a new thread by the due date for that module week. Posting the new thread as a response to the discussion question is part one of your grade for module discussions (i.e., Timeliness). 
• Part two of your grade for module discussion is your interaction (i.e., responding to classmate postings with thoughtful responses) with at least two classmates (i.e., Critical Thinking). This activity could go beyond the module week, but you should engage in this interaction by the due dates. 

Just posting your response to a discussion question is not sufficient; you need to interact with your classmates. Be detailed in your postings and in your responses to your classmates' postings. Feel free to agree or disagree with your classmates. Please ensure that your postings are civil and constructive. 

Assignments (40% of Final Grade Calculation)

Assignments will include a mix of qualitative assignments (e.g. literature reviews, summaries), and/or quantitative problem sets. Late submissions will be reduced by one letter grade for each week late (No exceptions without prior coordination with the instructors). 

Refer to the Assignment Rubric page for more detailed expectations and grading information.

Written Assignments

Include a cover sheet with your name and assignment identifier. Also include your name and a page number indicator (i.e., page x of y) on each page of your submissions. Each problem should have the problem statement, assumptions, computations, and conclusions/discussion delineated. All Figures and Tables should be captioned and labeled appropriately. All written assignments will be due as per the calendar dates posted in the Calendar each week. Typically, this is day 7 for each module, unless otherwise stated.

Coding Assignments

Students will be provided with raw data and will be challenged to write their own code. The code should be original and written with detailed comments, and can be easily executed by instructors, without warnings/errors. 

For each coding assignment, you will be expected to follow the instructions to submit brief report, if requested, or provide complete response to questions and include executable source code by the end of the Day 7 of the due module as mentioned in course outline document.  

You are encouraged to discuss/brainstorm among each other throughout the process; however, you should refrain from copying each other’s work or other sources and/or collaborating. You are also strongly discouraged from helping others in the form of already built code – in full or parts.

Quizzes (25% of Final Grade Calculation)

There will be 5 graded quizzes on weeks 3, 5, 8, 11, and 14.  These will be designed to check your preparation of required reading material and participation in reviewing video content etc. These will be counted towards a total of 25% points in your final grade.

Course Project (20% of Final Grade Calculation)

This course project involves researching, designing, and implementing a novel algorithm related to medical image processing. Students will work in groups to develop a project that addresses key learning objectives from the course, culminating in a detailed report and a presentation. The project integrates theoretical knowledge with practical skills, focusing on advanced image processing techniques such as image enhancement, segmentation, and registration using MATLAB or Python.  

The course project is worth 20% of your total course grade. The project is worth 100 points total, with each deliverable weighted as outlined in the Deliverables section. 

Refer to the Course Project Overview page for more detailed expectations and grading information.

Grading Policy

Assignments are due according to the dates posted in your Blackboard course site. You may check these due dates in the Course Calendar or the Assignments in the corresponding modules. I will post grades one week after assignment due dates.

A grade of A indicates achievement of consistent excellence and distinction throughout the course—that is, conspicuous excellence in all aspects of assignments and discussion in every week.

EP uses a +/- grading system (see “Grading System”, Graduate Programs catalog, p. 10).

Final grades will be determined by the following weighting:

Course Policies

Quizzes and written assignments should be completed by the student independently, without any assistance or the use of AI-based tools.

Academic Policies

Deadlines for Adding, Dropping and Withdrawing from Courses

Students may add a course up to one week after the start of the term for that particular course. Students may drop courses according to the drop deadlines outlined in the EP academic calendar (https://ep.jhu.edu/student-services/academic-calendar/). Between the 6th week of the class and prior to the final withdrawal deadline, a student may withdraw from a course with a W on their academic record. A record of the course will remain on the academic record with a W appearing in the grade column to indicate that the student registered and withdrew from the course.

Academic Misconduct Policy

All students are required to read, know, and comply with the Johns Hopkins University Krieger School of Arts and Sciences (KSAS) / Whiting School of Engineering (WSE) Procedures for Handling Allegations of Misconduct by Full-Time and Part-Time Graduate Students.

This policy prohibits academic misconduct, including but not limited to the following: cheating or facilitating cheating; plagiarism; reuse of assignments; unauthorized collaboration; alteration of graded assignments; and unfair competition. Course materials (old assignments, texts, or examinations, etc.) should not be shared unless authorized by the course instructor. Any questions related to this policy should be directed to EP’s academic integrity officer at ep-academic-integrity@jhu.edu.

Students with Disabilities - Accommodations and Accessibility

Johns Hopkins University values diversity and inclusion. We are committed to providing welcoming, equitable, and accessible educational experiences for all students. Students with disabilities (including those with psychological conditions, medical conditions and temporary disabilities) can request accommodations for this course by providing an Accommodation Letter issued by Student Disability Services (SDS). Please request accommodations for this course as early as possible to provide time for effective communication and arrangements.

For further information or to start the process of requesting accommodations, please contact Student Disability Services at Engineering for Professionals, ep-disability-svcs@jhu.edu.

Student Conduct Code

The fundamental purpose of the JHU regulation of student conduct is to promote and to protect the health, safety, welfare, property, and rights of all members of the University community as well as to promote the orderly operation of the University and to safeguard its property and facilities. As members of the University community, students accept certain responsibilities which support the educational mission and create an environment in which all students are afforded the same opportunity to succeed academically. 

For a full description of the code please visit the following website: https://studentaffairs.jhu.edu/policies-guidelines/student-code/

Classroom Climate

JHU is committed to creating a classroom environment that values the diversity of experiences and perspectives that all students bring. Everyone has the right to be treated with dignity and respect. Fostering an inclusive climate is important. Research and experience show that students who interact with peers who are different from themselves learn new things and experience tangible educational outcomes. At no time in this learning process should someone be singled out or treated unequally on the basis of any seen or unseen part of their identity. 
 
If you have concerns in this course about harassment, discrimination, or any unequal treatment, or if you seek accommodations or resources, please reach out to the course instructor directly. Reporting will never impact your course grade. You may also share concerns with your program chair, the Assistant Dean for Diversity and Inclusion, or the Office of Institutional Equity. In handling reports, people will protect your privacy as much as possible, but faculty and staff are required to officially report information for some cases (e.g. sexual harassment).

Course Auditing

When a student enrolls in an EP course with “audit” status, the student must reach an understanding with the instructor as to what is required to earn the “audit.” If the student does not meet those expectations, the instructor must notify the EP Registration Team [EP-Registration@exchange.johnshopkins.edu] in order for the student to be retroactively dropped or withdrawn from the course (depending on when the "audit" was requested and in accordance with EP registration deadlines). All lecture content will remain accessible to auditing students, but access to all other course material is left to the discretion of the instructor.