RT Conference Proceedings
T1 PET image classification using HHT-based features through fractal sampling
A1 Ortiz-García, Andrés
A1 Lozano, Francisco
A1 Peinado-Domínguez, Alberto
A1 García, María
K1 Medicina - Procesado de imágenes
AB Medical image classification is currently a challenging task  that can be used to aid the diagnosis of different brain diseases. Thus,  exploratory and discriminative analysis techniques aiming to obtain rep-  resentative features from the images, play a decisive role in the design  of effective Computer Aided Diagnosis (CAD) systems, which is spe-  cially important in the early diagnosis of dementias. In this work we  present a technique that allows extracting discriminative features from  Positron Emission Tomography (PET) by means of an Empirical Mode  Decomposition-based (EEMD) method. This requires to transform the  3D PET image into a time series which is addressed by sampling the  image using a fractal-based method which allows to preserve the spa-  tial relationship among voxels. The devised technique has been used  to classify images from the Alzheimer's Disease Neuroimaging Initiat-  ive (ADNI) achieving up to a 90.5% accuracy in a differential diagnosis  task (AD vs. controls), which proves that the information retrieved by  our methodology is significantly linked to the disease.
YR 2017
FD 2017-07-06
LK http://hdl.handle.net/10630/14137
UL http://hdl.handle.net/10630/14137
LA spa
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026