M,W: 10:10 a.m. - 11:25 a.m.
Room: 1104

Instructor: Juan Franquiz
Office: EAS 2612
Office hours: M and W, from 8:00 a.m. to 10:00 a.m.
Phone number: 348 - 6112
Email: franquiz@fiu.edu

Course Description: The course introduces students in the basic concepts and methods for image analysis in biomedical engineering and medical physics. Use of basic software for image analysis in biomedical engineering and medical physics.

Course Objectives:
1) Provide the basic concepts and methods in which medical image analysis is based.
2) Introduce some of the most commonly used software tools for image analysis in biomedical engineering and medical physics.
3) Provide the methodology and algorithms for 3D reconstruction and display of medical images.
4) Provide the basic concepts and methodologies of using images for computer aided diagnosis (CAD).

Learning Objectives:
At the end of the course, the student should be able to:
1) Define and explain the major concepts and methods used for image analysis in biomedical engineering and medical physics.
2) Understand the methods and algorithms used for 3D reconstruction and display of medical images.
3) Understand and use the major commercial software tools used for image analysis in biomedical engineering.
4) Understand the basic concepts and methodologies used of computer aided diagnosis (CAD) with medical images.

Textbook: Class notes and materials and materials delivered by the instructor.

Grade Distribution:
Homework 50%
Projects (3) 50%

Homework will be due two weeks after the date they are assigned. Late homework assignments will loss 50% of their initial grade.

Course Program:

May 7 Class 1: Basic concepts in analysis of medical images: brightness, contrast, dynamic range, spatial resolution and noise.

May 12 Class 2: Assessment of the performance of medical imaging systems. Linearity and optical transfer function.

May 14 Class 3: Practical determination of the optical transfer function.

May 19 Class 4: Digital Image. Sampling, quantization, spatial aliasing and brightness resolution. Spatial frequency transformations and Nyquist frequency.

May 21 Class 5: DICOM format of digital medical images. Medical imaging modalities and picture archiving communication systems (PACS).

May 26 No Class - Memorial Day.

May 28 Class 6: Basic algorithms and software for analysis of medical images.

June 2 Class 7: Three dimensional (3D) reconstruction of medical images. The Radon transform and the filtered backprojection method.

June 4 Class 8: Practical implementation of the filtered backprojection method.

June 9 Class 9: Practical applications and limitations of the filtered backprojection method.

June 11 Class 10: Theoretical basis of image reconstruction by iterative numerical methods.

June 16 Class 11: Practical implementation of an iterative reconstruction method.

June 18 Class 12: Practical implementation of corrections in an iterative reconstruction algorithm.

June 23 No Class - working in projects.

June 25 No class - working in projects.

June 30 Class 13: Methods for the 3D display of medical images. Examples and applications.

Juyl 2 Class 14: Practical implementation of volume rendering for 3D display of medical images.

July 7 Class 15: Practical implementation of surface shading and surface modeling for 3D display of medical images.

July 9 Class 16: Methods and algorithms for registration of medical images.

July 14 Class 17: Methods and algorithms for validating the registration of medical images.

July 16 Class 18: Methods and algorithms for analysis of functional images - Fourier analysis of cardiac motion.

July 21 Class 19: Methods and algorithms for analysis of functional images - functional magnetic resonance imaging (fMRI).

July 23 Class 20: Methods for assessing the diagnostic performance of medical imaging modalities. The receiver operating characteristic (ROC) curve.

July 28 Class 21: Basic concepts and methods for computer aided diagnosis using medical images.

July 30 Class 22: Basic computational algorithms for computer aided diagnosis using medical images.

Aug 4 Class 23: Practical applications of computer aided diagnosis using medical images.

Aug 6 Class 24: Summary of the course.