Lab 1

Image processing in MATLAB and PYTHON

  • MATLAB exercises for Lab 1: [PDF]. Data: patient_data.csv, mri.png
  • Outline  [PPTX] [PDF]
  • dcm2nii DICOM to NIfTI conversion   |   NiBabel  Access various neuro-imaging file formats with Python
  • MATLAB tools for NIfTI and ANALYZE image
  • Even better MATLAB toolbox for NIfTI by Xiangrui Li:  dicm2nii (with friends) 
  • Comparing MATLAB / PYTHON / R commands [ PDF ]
  •  [ iep ] - the Interactive Editor for Python (a simple and efficient cross-platform Python IDE focused on interactivity and introspection, which makes it very suitable for scientific computing)
  • RStudio ] - a free and open source integrated development environment (IDE) for R
  • A. McAndrew: An Introduction to image processing with MATLAB  [ PDF ]
  • Programming Computer Vision with Python (Jan Erik Solem)  [link]
  • Neuroimaging in Python (community site)  [NIPY]
  • Sage in medical imaging
  • ITK-SNAP for segmenting structures in 3D medical images
  • Links to relevant software for medical imaging and data analysis

Lab 2

Multispectral imaging and tissue classification (machine learning)
  • Introduction to pattern recognition  [PPTX]  [PDF]
  • Erickson et al. 2017 "Machine Learning for Medical Imaging"  [PDF]
  • Statistics & Machine Learning with MATLAB at MathWorks
  • Statistics & Machine Learning with Python [Statsmodels[scikit-learn[pandas]  [PyMVPA]
  • Statistics & Machine Learning with R at CRAN
  • Part 1 - "Contrast to noise ratio"  [DOCX] [PDF]
  • Part 2 - "Supervised and unsupervised classification" [DOCX] [PDF]
            cf. Wikipedia:  k-nearest neighbour algorithm  and  k-means clustering
                                   and Machine learning
  • Lundervold et al. 2000 paper
  • Multispectral MRI data from the paper (now also including the 3D NIFTI files)
  • All files (m-files and image data) for Lab 2: 
  • Link to "DICOM to NIfTI converter, NIfTI tool and viewer" by Xiangrui Li on MathWorks File Exchange (a very useful toolkit for NIfTI conversion, visualisation and transformation !)

Lab 3

Processing of diffusion MRI data   (DTI and DSI)

Lab 4

Processing of dynamic susceptibility contrast MR images (DSC-MRI) 
  • Lab 4 demo (incl. m-files and 4D brain, kidney, heart data)  ( 
  • Convolution - conv_residue_function_bmed360.m (cf. Tofts 2003, Fig. 11.6
  • Convolution and Sampling, EEN307 UMiami [PDF]
  • Koh et al, 2011 review JMRI paper
  • Heart perfusion MRI simulator (Aja-Fernandez: Matlab Central, IEEE ISBI 2012 paper)
  • Emblem et al. Vessel architectural imaging identifies cancer patient responders to anti-angiogenetic therapy. Nature Medicine 2013;19:1178-1183  [PDF]

Lab 5

Vascular permeability mapping and Dynamic T1-weighted Contrast Enhanced MRI

Lab 6

Estimation and visualization of structural and functional brain connectivity

  • Brain connectivity in cognitive aging - intro and demo [PPTX] [PDF]
  • Functional connectivity data [FC651.mat]  from Ystad et al. (2010)
  • Functional connectivity calculation [fc_subj651.m]  [PDF]  from Ystad et al. (2010)
  • Ystad M, Eichele T, Lundervold AJ, Lundervold ASubcortical functional connectivity and verbal episodic memory in healthy elderly - A resting state fMRI study. Neuroimage 2010;52(1):379-388. [PubMed] [PDF]
  • Pajek Program for Large Network Analysis
  • Time Series Analysis for Neuroscience in Python  [Nitime]
                    Suggested processing tools:    aMRI: FreeSurfer    dMRI: DSI Studio     rs-fMRI: CONN 
                                            NIfTI tool and viewer for MATLAB at MathWorks File Exchange is [here]

Midterm project  (Kiwifruit seed segmentation)   [ PDF ] [ PPTX ]  (segmentation methods)