BME42-731/ECE18-795/CB02-740 Bioimage Informatics (12 Units) Spring 2012 Instructor Ge Yang, Ph.D. Assistant professor, Department of Biomedical Engineering Assistant professor, Lane Center for Computational Biology Instructor Contact Information - Email – [email protected] - Telephone – 412-268-3186 - Office Location – Mellon Institute 403 - Preferred communication approach is by email. Please include BME42-731 in the subject. Instructor Office Hour & Location 1:00PM – 2:00PM Friday or by appointment Mellon Institute 403 Pre-requisite or Co-requisite - Image processing; Background in computer vision and/or medical image analysis is very helpful but not essential. - Proficiency in programming; Familiarity with MATLAB is very helpful but not essential. Class Times & Locations - Monday & Wednesday, 11:30AM - 12:50PM, Doherty Hall 1209 Class Website - http://www.andrew.cmu.edu/course/42-731/ Teaching Assistant(s) and Contact Information: Anuparma Kuruvilla Email: [email protected] Office: C119 Hamerschlag Hall Directions: http://www.cbi.cmu.edu/contact/directions/index.html Office hour: Not assigned; By appointment. Course description & objectives Development of biology over the past half a century has made it possible to identify the complete set of genes and proteins of a live organism. The complex interactions between these molecules in space and time define life. These interactions can now be visualized using fluorescence microscopy techniques, whose development represents one of the most fundamental and exciting advances in biomedical science and engineering over the past two decades. However, without quantitative measurement, fluorescence microscopy is restricted to a tool of visualization. The field of bioimage informatics is created over the past few years with the goal of applying computation, statistical analysis, and engineering techniques to effectively manage, visualize, analyze, and eventually understand the tremendous amount of image data generated routinely using fluorescence microscopy in contemporary biomedical research. Highly interdisciplinary in nature, bioimage informatics provides exciting opportunities forstudents with solid analytical and/or engineering skills to make fundamental contributions in research and development. The main purpose of this class is to prepare students for such opportunities through course training. Specifically, by completing the training of this course, the students should be able to - Understand basic concepts and principles of bioimage informatics. - Understand fundamentals of fluorescent microscopy. - Apply basic image processing and computer vision techniques in fluorescence image data analysis. - Apply basic statistical analysis and information extraction techniques in fluorescence image data understanding. Required Textbook(s) None. Recommended References Image processing & computer vision - Szeliski, Computer vision: algorithms and applications, Springer, 2010. - Gonzalez & Woods, Digital image processing, 3rd ed., Prentice Hall, 2007. - Snyder & Qi, Machine vision, Cambridge University Press, 2004. - Sonka, Hlavac, & Boyle, Image processing, analysis, and machine vision, CL- Engineering, 2007. Optics - Hecht, Optics, 4th ed. (or 3rd ed), Addison Wesley, 2001. - Born & Wolf, Principles of optics, 7th ed., Cambridge University Press, 1999. Light & fluorescence microscopy - Herman, Fluorescence microscopy, 2nd ed., Taylor & Francis, 1998. - Inoue & Spring, Video microscopy, 2nd ed., Plenum Press, 1997. This list is not exhaustive as there are other excellent references. A substantial collection of additional reference materials, including research papers and online information, will be distributed in class or posted on the course web page. Classroom Policy - Lectures will start and end on time. If you are late, you should enter the class without causing disruptions. - Use of cell phones during class is prohibited. - Class participation will be considered in grading, especially when a student’s grade is borderline between two tiers (e.g. A- versus B+). Academic Integrity - University regulations will be followed. See http://www.studentaffairs.cmu.edu/acad_integ/acad_integ_text.html Reading and Project Assignments: - Instructions for reading and project assignments will be handed out in class.- Completed reading and project assignments must be submitted before deadline. Late assignments will not be accepted. Exception will only be considered on a case-by-case basis by the instructor. Grading* Reading assignment (5 in total) 40% Project assignment (4-5 in total) 50% Class participation* 10% Total 100% * - The instructor reserves the rights to make small adjustments to the percentage scores. * - Students are expected to attend lectures. Repetitive (>3) absences from lectures without instructor approval will result in up to 10% deduction of final grade. * - Policy regarding absence from your group presentations without approval by the instructor before the class. - First time: warning; 10% deduction of final percentage grade - Second time: warning; final grade lowered by one tier (i.e. AB; BC) - Third time: automatic failure List of topics Note: For reference only. Adjustments are likely as the class proceeds. Lecture Topics Lecture 1 Introduction Lecture 2 Fundamentals of light microscopy Lecture 3 Practical issues in bioimage informatics Lecture 4 Fundamentals of fluorescence microscopy Lecture 5 Applications of fluorescence microscopy Lecture 6 Literature review Lecture 7 Lab visit: fluorescence microscopy Lecture 8 Bioimaging data analysis: point feature detection Lecture 9 Bioimaging data analysis: line/curve detection Lecture 10 Project presentation & review Lecture 11 Bioimaging data analysis: registration Lecture 12 Bioimaging data analysis: segmentationLecture 13 Literature review Lecture 14 Bioimaging data analysis: tracking Lecture 15 Project presentation & review Lecture 16 Bioimaging data analysis: image database Lecture 17 Bioimage analysis: information extraction Lecture 18 Bioimage analysis: data mining Lecture 19 Special focus I: Statistical methods for bioimaging informatics Lecture 20 Special focus II: High-throughput screening Lecture 21 Literature review Lecture 22