A tool for shape-based registration in fully automated SPECT imaging quantification protocols.

PySBR is a tool implemented in python that provides a fully automated approach to achieve SPECT to SPECT shape-based matching. Specifically, the tool comprises the following parts:

1. A fast intensity-based registration workflow using nipype and ANTS (http://stnava.github.io/ANTs/) to search for an affine transformation that initialises non-linear registration;
2. an image-to-atlas registration process, in which we optimise a metric based on shape analysis of the image to hierarchically locate a set of landmarks of interest;
3. a resampling module to map the subject’s image to the template

We are deciding the final availability of datasets, we will post here the url soon.

Papers making use of PySBR should cite:

Papers making use of the template released alongwith PySBR should cite:

Papers making use of the datasets released alongwith PySBR should cite:

PySBR methodology and implementation: Oscar Esteban, Gert Wollny

Template building: Aida Niñerola-Baizán

Simulated database: Judith Gallego, Albert Cot

Quantification software: Aida Niñerola-Baizán, Berta Martí-Fuster

Clinical application and supervision: Francisco Lomeña (flomena@clinic.ub.es)

Senior researchers: Francisco Lomeña (flomena@clinic.ub.es, Xavier Setoain (setoain@clinic.ub.es), Javier Pavía (jpavia@clinic.ub.es), Domènec Ros (dros@ub.edu), Andrés Santos (andres@die.upm.es), M.-Jesús Ledesma-Carbayo (mledesma@die.upm.es)

This work was supported in part by Multimodal Imaging tools for Neurological Diseases (MIND-t) project of Biomedical Research Networking center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), by Spain’s Ministry of Science and Innovation through SAF2009- 08076, TEC2011-28972-C02-02, IPT-300000-2010-003 and CDTICENIT (AMIT project) and Fondo de Investigaciones Sanitarias (PI12-00390). B. Martí-Fuster was awarded a PhD fellowship (App Form Call 07-2009) of Institute for Bioengineering of Catalonia (IBEC).