Image Analysis & Machine Learning for Microscopy Course

Lecturer: Dani Ushizima, Ph.D.
Venue: 2017 UC Berkeley Brain Microscopy
4d-advanced-microscopy-of-brain-circuits

The Zeiss Berkeley Brain Microscopy Innovation Center at the University of California, Berkeley offers an annual course on state-of-the-art optical tools, imaging systems, and analysis methods that are being developed for the study of neuronal circuits. The intensive week-long course includes training in the theory and practice of emerging BRAIN Initiative neurotechnologies. This course targets the main steps to develop a end-to-end pipeline/workflow for image understanding. Lecture slides: DOWNLOAD.

Outline:

Image format and metadata
Image enhancement and filtering
Image statistics
Image segmentation: super-pixel to object
Object description
Object classification
Object visualization

Code:

Books/papers:

Burger et al, Digital Image Processing, 2007 [sample]
Goodfellow, Bengio, Courville [book]
Other Machine Learning [books]
Ushizima in [brain] [neuron] [cervical cell] [ceramics]

Software:

ImageJ/Fiji
- Macro manual
Python
- Scipy for images
- Scikit-image
- Free books
R
- EBImage package
- Medical image analysis
- Rattle data mining, brochure
TomViz

Datasets

Neurons/Immunofluorescence

dani-lbnl/2017_ucberkeley_course