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Laboratorio de Imagen Médica (Medical Imaging Laboratory)'s Projects

able icon able

Automated Brain Lines Extraction Based on Laplacian Skeletonization

ants icon ants

Advanced Normalization Tools (ANTs)

chimera icon chimera

Chimera Algorithm, a novel optimizer able to generate and evolve the architecture of feedforward Convolutional Neural Networks based on the adaptation of the Artificial Bee Colony Algorithm to work within an Evolutionary Computation framework

conosurf icon conosurf

An open-source 3D scanning system based on a conoscopic holography device for acquiring surgical surfaces

efficient-art-split-bregman-reconstruction icon efficient-art-split-bregman-reconstruction

MATLAB code for an iterative reconstruction method that alternates a computationally efficient linear solver (ART) with a fast denoising step based on the Split Bregman formulation

j.cmpb.2013.04.010 icon j.cmpb.2013.04.010

Source code for paper "Automatic TAC extraction from dynamic cardiac PET imaging using iterative correlation from a population template"

jclustering icon jclustering

jClustering is a dynamic image clustering framework for ImageJ. It provides a public API for implementing new clustering algorithms and several implementations.

limtools icon limtools

ImageJ plugins and macros developed at the Medical Imaging Laboratory

nir icon nir

Code for Asier Thesis

pointsetprocessing icon pointsetprocessing

A set of classes (vtkPointSetOutlierRemoval, vtkPointSetNormalEstimation, vtkPointSetNormalOrientation, vtkPointSetCurvatureEstimation, vtkEuclideanMinimumSpanningTree, and vtkRiemannianGraphFilter) to enable several basic operations on point sets. These classes are implemented as VTK filters.

swim icon swim

Vertex-wise Sulcal Width Map Estimation

tracerkinetic icon tracerkinetic

This R package implements compartmental models and linear approximations needed to perform kinetic analysis on dynamic medical images. The provided functions use the tissue time-activity curves, the input function and the frame times as input, and return the kinetic parameters and the estimated errors.

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