Computational Methods for Biomedical Image Analysis and Interpretation
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Course Description
The latest biological and medical imaging modalities and their applications in research and medicine. Focus is on computational analytic and interpretive approaches to optimize extraction and use of biological and clinical imaging data for diagnostic and therapeutic translational medical applications. Topics include major image databases, fundamental methods in image processing and quantitative extraction of image features, structured recording of image information including semantic features and ontologies, indexing, search and content-based image retrieval. Case studies include linking image data to genomic, phenotypic and clinical data, developing representations of image phenotypes for use in medical decision support and research applications and the role that biomedical imaging informatics plays in new questions in biomedical science. Includes a project. Enrollment for 3 units requires instructor consent. Prerequisites: programming ability at the level of CS 106A, familiarity with statistics, basic biology. Knowledge of Matlab or Python highly recommended.
Cross Listed Courses
Grading Basis
MOP - Medical Option (Med-Ltr-CR/NC)
Min
3
Max
4
Course Repeatable for Degree Credit?
No
Course Component
Lecture
Enrollment Optional?
No
Does this course satisfy the University Language Requirement?
No
Programs
BIOMEDIN260
is a
completion requirement
for: