PHD Sample Program - Biomedical Engineering at CIS

Year 1

1st year Medical School basic sciences curriculum. (Molecules and Cells, Immunology, Neuroscience, and Physiology). This program fulfills the biology curriculum, although students will usually want to take additional advanced seminars in neuroscience. These courses usually fill a student's time during the first year and are supplemented with rotations.

Year 2 or Years 1 & 2 Electives in the Engineering and Physical Sciences

The following curriculum is to be completed in Year 2 if taking the SOM basic life sciences track or in Years 1-2 if taking the alternative track. Students are required to take at least 2 courses per semester in Year 2, with at least one of these being at the 600/700 level. Curricula are to be designed with the guidance of the student's mentor. Suggested electives are given below for each track (choose 4 of 6 each semester). Qualifiers are taken either at the end of the second year or in the middle of the third year.

    Medical Imaging Systems

    Fall

  • 110.405 Analysis I
  • 520.414 Image Processing and Analysis I
  • 520.651 Random Signals
  • 550.420 Introduction to Probability
  • 550.437 Information, Statistics and Perception
  •      TBN (Radiology)

    • Spring

  • 110.406 Analysis II
  • 520.415 Image Processing and Analysis II
  • 550.426 Stochastic Processes
  • 580.472 Medical Imaging Systems
  •      TBN (Radiology)
  •      TBN (Radiology)

    Computational Vision and
    Image Understanding

    Fall

  • 110.405 Analysis I
  • 520.414 Image Processing and Analysis I
  • 520.651 Random Signals
  • 550.420 Introduction to Probability
  • 550.437 Information, Statistics and Perception
  • 600.357 Computer Graphics

    • Spring

  • 110.406 Analysis II
  • 520.415 Image Processing and Analysis II
  • 520.630 Introduction to the Calculus of Variations and Optimal Control
  • 520.652 Filtering & Smoothing
  • 550.426 Stochastic Processes
  • 550.730 Topics in Statistics: Statistical Pattern Recognition

    Geometry, Shape and
    Computational Anatomy

    Fall

  • Research Project (3 credits)
  • Pick 1 course from the list below

    • Spring

  • Research Project (3 credits)
  • Pick 1 course from the list below
  • Dissertation

Year 3 (Choose 4 of following) and Year 4 (Choose 2 of following)

    Applied Mathematics and Statistics

  • 550.361 Linear Optimization
  • 550.420 Introduction to Probability
  • 550.426 Introduction to Stochastic Processes
  • 550.430 Introduction to Statistics
  • 550.434 Nonparametric and Robust Methods
  • 550.437 Statistics, Information and Perception
  • 550.620 Probability Theory I
  • 550.621 Probability Theory II
  • 550.626 Stochastic Processes II
  • 550.630 Statistical Theory
  • 550.631 Statistical Inference
  • 550.632 Multivariate Statistical Theory
  • 550.633 Time Series Analysis
  • 550.634 Nonparametric and Robust Inference
  • 550.661 Foundations of Optimization
  • 550.662 Optimization Algorithms
  • 550.672 Graph Theory
  • 550.681 Numerical Analysis
  • 550.692 Matrix Analysis and Linear Algebra
  • 550.723 Markov Chains
  • 550.730 Topics in Statistics: Statistical Pattern Recognition
  • 550.764 Optimization of Functionals
  • 550.790 Topics in Applied Mathematics: Deformation Analysis for Images and Shapes

    Mechanical Engineering

  • 530.601 Continuum Mechanics
  • 530.648 Group Theory in Engineering Design
  • 530.669 Computational Methods of Engineering

    Biomedical Engineering

  • 580.473 Magnetic Resonance in Medicine
  • 580.472 Medical Imaging Systems
  • 580.744 Pattern Theory: From representation to Inference

    Electrical and Computer Engineering

  • 520.414 Image Processing and Analysis I
  • 520.415 Image Processing and Analysis II
  • 520.432 Medical Imaging Systems
  • 520.435 Digital Signal Processing
  • 520.447 Introduction to Information Theory and Coding
  • 520.497 Information Theory
  • 520.608 Image Reconstruction and Restoration
  • 520.614 Linear Systems Theory
  • 520.630 Introduction to the Calculus of Variations and Optimal Control
  • 520.643 Digital Multimedia Coding and Processing
  • 520.644 Pattern Theory: From representation to Inference
  • 520.645 Adaptive Filtering
  • 520.646 Wavelets and Filter Banks
  • 520.651 Random Signal Analysis
  • 520.652 Filtering and Smoothing
  • 520.674 Information Theoretic Methods in Statistics

    Bioethics Elective

  • 306.655 Ethical Issues in Public Health

    Computer Science

  • 600.303 High Performance Computing
  • 600.357 Computer Graphics
  • 600.441 Vision-Based Interaction for Man and Machine
  • 600.445 Computer-Integrated Surgery I
  • 600.446 Computer-Integrated Surgery II
  • 600.461 Computer Vision
  • 600.462 Applications of Computer Vision
  • 600.630 Advanced Topics in Physics-Based Computer Vision
  • 600.646 Advanced Computer-Integrated Surgery
  • 600.652 Advanced Computer-Integrated Surgery Seminar
  • 600.746 Medical Image Analysis Seminar

    Mathematics

  • 110.405 Analysis I
  • 110.406 Analysis II
  • 110.413 Introduction to Topology
  • 110.417 Partial Differential Equations for Applications
  • 110.423 Lie Groups
  • 110.427 Introduction to Calculus of Variation
  • 110.439 Introduction to Differential Geometry
  • 110.605 Real Variables
  • 110.619/110.620 Lie Groups and Lie Algebras
  • 110.631/110.632 Partial Differential Equations
  • 110.645/110.646 Riemannian Geometry

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