Period: 2nd (Spring semester)
ECTS: 4
Course contents:
Topic 1: Elementary concepts
1. Bit, byte, pixel, voxel, formats of image, dynamic range, histogram, LUTs, mathematical operations with images.
2. Sampling: theorem of Shannon-Whittaker-Nyquist.
3. Fourier’s space, operations in the space of frequency with images.
4. Segmentation, types of noise and filters in the real and Fourier spaces.
5. Projection and back-projection.
6. Visualization 3D, ImageJ’s utilization, use of plugins, Macro programming.
Topic 2: Quantification of the image
1. Densitometry.
2. Granulometry
Topic 3: Signal processing and analysis
1. Periodic signal, 2D crystals, stacks, helix: periodic signals, lattice vectors, stacks and helix parameters.
2. Signal to noise ratio.
3. Denoising
Topics 4: 3D Reconstruction from projections
1. Reconstruction algorithms used in diagnosis by images and biology: theorem of the central section, back-projection in Fourier’s space, weighted back-projection, algebraic reconstruction technics.
2. Effects of sub-sampling and loss of information.
Topic 5: Return and segmentation of volumes
1. Manual segmentation.
2. Semi-automatic segmentation
Bibliography:
Recommended textbooks:
⋅Electron tomography. J Frank. Ed Springer. 2nd edition. ISBN: 0-387-31234-X
⋅Digital Image processing. An algorithmic introduction using Java. W. Burger & M.J. Burge. Ed. Springer. ISBN: 978-1-84628-379-6
Faculty:
Coordinador: Sergio Marco Garrido
Email: sergio.marco@sanofi.com
Website: http://fr.linkedin.com/pub/sergio-marco-garrido/83/164/3a/
More info on the course official guide (Guía docente)