First year medical school basic sciences curriculum. This program fulfills the biology curriculum, and 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.
The following curriculum is to be completed in year two if taking the SOM basic life sciences track, or in years one/two if taking the alternative track. Students are required to take at least two courses per semester in year two, 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 four of six each semester). Qualifiers are taken either at the end of the second year or in the middle of the third year.
Medical Imaging Systems | Computational Vision and Image Understanding | Geometry, Shape and Computational Anatomy |
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Fall | Fall | Fall |
110.405 Analysis I | 110.405 Analysis I | Research Project (3 credits) |
520.414 Image Processing and Analysis I | 520.414 Image Processing and Analysis I | Pick 1 course from the list below |
520.651 Random Signals | 520.651 Random Signals | |
550.420 Introduction to Probability | 550.420 Introduction to Probability | |
550.437 Information, Statistics and Perception TBN (Radiology) | 550.437 Information, Statistics and Perception | |
600.357 Computer Graphics | ||
Spring | Spring | Spring |
110.406 Analysis II | 110.406 Analysis II | Research Project (3 credits |
520.415 Image Processing and Analysis II | 520.415 Image Processing and Analysis II | Pick 1 course from the list below |
550.426 Stochastic Processes | 520.630 Introduction to the Calculus of Variations and Optimal Control | Dissertation |
580.472 Medical Imaging Systems | 520.652 Filtering & Smoothing | |
TBN (Radiology) | 550.426 Stochastic Processes | |
TBN (Radiology) | 550.730 Topics in Statistics: Statistical Pattern Recognition |
Applied Mathematics and Statistics | Electrical and Computer Engineering | Computer Science |
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550.361 Linear Optimization | 520.414 Image Processing and Analysis I | 600.303 High Performance Computing |
550.420 Introduction to Probability | 520.415 Image Processing and Analysis II | 600.357 Computer Graphics |
550.426 Introduction to Stochastic Processes | 520.432 Medical Imaging Systems | 600.441 Vision-Based Interaction for Man and Machine |
550.430 Introduction to Statistics | 520.435 Digital Signal Processing | 600.445 Computer-Integrated Surgery I |
550.434 Nonparametric and Robust Methods | 520.447 Introduction to Information Theory and Coding | 600.446 Computer-Integrated Surgery II |
550.437 Statistics, Information and Perception | 520.497 Information Theory | 600.461 Computer Vision |
550.620 Probability Theory I | 520.608 Image Reconstruction and Restoration | 600.462 Applications of Computer Vision |
550.621 Probability Theory II | 520.614 Linear Systems Theory | 600.630 Advanced Topics in Physics-Based Computer Vision |
550.626 Stochastic Processes II | 520.630 Introduction to the Calculus of Variations and Optimal Control | 600.646 Advanced Computer-Integrated Surgery |
550.630 Statistical Theory | 520.643 Digital Multimedia Coding and Processing | 600.652 Advanced Computer-Integrated Surgery Seminar |
550.631 Statistical Inference | 520.644 Pattern Theory: From representation to Inference | 600.746 Medical Image Analysis Seminar |
550.632 Multivariate Statistical Theory | 520.645 Adaptive Filtering | |
550.633 Time Series Analysis | 520.646 Wavelets and Filter Banks | |
550.634 Nonparametric and Robust Inference | 520.651 Random Signal Analysis | |
550.661 Foundations of Optimization | 520.652 Filtering and Smoothing | |
550.662 Optimization Algorithms | 520.674 Information Theoretic Methods in Statistics | |
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 | Biomedical Engineering | Mathematics |
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530.601 Continuum Mechanics | 580.473 Magnetic Resonance in Medicine | 110.405 Analysis I |
530.648 Group Theory in Engineering Design | 580.472 Medical Imaging Systems | 110.406 Analysis II |
530.669 Computational Methods of Engineering | 580.744 Pattern Theory: From representation to Inference | 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 Algebra | ||
110.631/110.632 Partial Differential Equations | ||
110.645/110.646 Riemannian Geometry |
Bioethics Elective | ||
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306.655 Ethical Issues in Public Health |