Biomedical Image Analysis (6ΚΒ06)
Instructor : Dimitrios Iakovidis
Course typeElective
Semester6
TermSpring Semester
ECTS5
Teaching hours3
Laboratory hours1
Description
Introduction to digital image processing and analysis with applications in biomedicine. Digital image representation and synthesis. Image sampling and regions of interest. Geometric transformations. Operators. Global and local intensity transformations. Convolution, filters, two-dimensional discrete Fourier transform, and discrete wavelet transform. Morphological transformations. Introduction to color image processing, color theory and color spaces. Image enhancement, segmentation and compression algorithms. Color, texture ad shape feature extraction algorithms. Saliency and object detection algorithms. Applications on various kinds of biomedical images, including endoscopic, ultrasound, x-ray, tomography and DNA microarray images.
Course objectives
  • Comprehension of the main concepts of image processing and analysis.
  • Learning the mathematical formalism and the main filters/operators processing and analysis.
  • Acquiring abilities to implement algorithms for processing and analysis of biomedical images.
  • Analyzing relevant problems and selection of the proper filters/operators.
  • Understanding the requirements specific to processing and analysis of biomedical images.
Textbooks/Bibliography
  • Ψηφιακή Επεξεργασία Εικόνας, Gonzales, ΕΚΔΟΣΕΙΣ Α. ΤΖΙΟΛΑ & ΥΙΟΙ Α.Ε. , 3η έκδ./2010, ΘΕΣ/ΝΙΚΗ
  • Ψηφιακή Επεξεργασία και Ανάλυση Εικόνας, Νικόλαος Παπαμάρκος, ΝΙΚΟΛΑΟΣ ΠΑΠΑΜΑΡΚΟΥ, 3η/2013, ΑΘΗΝΑ
  • Ψηφιακή Επεξεργασία Εικόνας, ΙΩΑΝΝΗΣ ΠΗΤΑΣ,ΙΩΑΝΝΗΣ ΠΗΤΑΣ, 2η/2010, ΘΕΣ/ΝΙΚΗ
  • «Digital Image Processing», R. Gonzalez, R. Woods, 2nd ed. 2002.
  • «Practical Algorithms for Image Analysis: Descriptions, Examples, and Code», M. Seul, L. O'Gorman, M. Sammon.
  • «Fundamentals of Digital Image Processing», A. Jain.
Assessment method
Written examinations at the end of the semester Submission of laboratory exercises Laboratory examination