Diagnostic radiology requires accurate interpretation of complex signals in medical images.
Content-based image retrieval (CBIR) techniques could be valuable to radiologists in …

Functional magnetic resonance imaging (fMRI) is a fairly new technique that has the
potential to characterize and classify brain disorders such as schizophrenia. It has the …

Effective diagnosis of Alzheimer's disease (AD) is of primary importance in biomedical
research. Recent studies have demonstrated that neuroimaging parameters are sensitive …

Determining the health of muscle cells by in vivo imaging could impact the diagnosis and
monitoring of a large number of congenital and acquired muscular or cardiac disorders …

Classification of subjects into predefined groups, such as patient vs. control, based on their
functional MRI data is a potentially useful procedure for clinical diagnostic purposes. This …

In this paper we propose a new method for classification of subjects into schizophrenia and
control groups using functional magnetic resonance imaging (fMRI) data. In the …

The massive generation of data has raised new research topics, such as methods to store
and to retrieve large volumes of information. Some medical image modalities, such as …

In this paper we propose a novel approach for detection, segmentation and characterization
of brain tumors. Our method exploits prior knowledge in the form of a sparse graph …

Various approaches have been taken to detect anomalies, with certain particularities in the
medical image scenario, linked to other terms: content-based image retrieval, pattern …

Pattern recognition approaches to the analysis of neuroimaging data have brought new
applications such as the classification of patients and healthy controls within reach. In our …