GUI for granule segmentation in TEM images

Link added to Matlab code for the algorithm proposed in: David Nam, Judith Mantell, David Bull, Paul Verkade, Alin Achim, A Novel Framework for Segmentation of Secretory Granules in Electron Micrographs, Medical Image Analysis, Volume 18, Issue 2, February 2014, pp. 411-424.

See Software section for details.

Bayesian MAE image denoising code made available

13 years after the publication of my IEEE TMI paper on Bayesian denoising of ultrasound images with alpha-stable distributions I still get the odd request for the code that implements that algorithm. I have today finally decided that it is more efficient to have it up on a website than keep e-mailing it … 😐 You can find it in the ‘Software‘ section of the website, while below are some explanations, copied and pasted from the e-mail I kept copying and pasting for all these years:

Dear …,

Thank you for your interest in our work.
I’m sending attached some of my code which will hopefully help you re-implement the method in that paper. Please note however that not all the attached code is the one used to derive the results therein as I lost some of the original files during my trips from one institution to another across Europe before getting my current job. The main differences are:

  • In order to run the code, you’ll need to go to and download the matlab implementation of the dual-tree DWT. My original implementation used the separable DWT embedded into the cycle-spinning algorithm.
  • In the present form, my code does additive noise removal. If you want to remove speckle you’ll need to use a log transformation in the beginning and an exponential one at the end.
  • In the main function, line 67 reads im = stablepdf(x1,alpha,0,disp,0,2); I cannot provide you the code for calculating stable density functions as at the time it was provided to me by John Nolan under promise that I won’t recirculate it. You would thus need to go to and buy the STABLE code … (or write your own function to compute stable densities)

Hope this helps!