Susana Merino-Caviedes

  • Citations Per Year
Learn More
This paper proposes a methodology for the joint alignment of a sequence of images based on a groupwise registration procedure by using a new family of metrics that exploit the expected sparseness of the temporal intensity curves corresponding to the aligned points. Therefore, this methodology is able to tackle the alignment of temporal sequences of images(More)
Classic geometric active contour algorithms have the limitation of segmenting the image into only two regions: background and object of interest. A new multiphase level set algorithm for the segmentation of two or more regions of interest is proposed. This algorithm avoids by construction the presence of overlapped and void regions and no additional(More)
Delayed Enhancement Magnetic Resonance (DE-MR) has clinical relevance in the diagnosis and prognosis of several cardiomyopathies with different etiologies, since they often lead to different scar configurations. However, to the best of our knowledge very little research has been devoted to the computational characterization of the scar islands detected by(More)
We propose a fully 3-D methodology for the computation of myocardial nonviable tissue transmurality in contrast enhanced magnetic resonance images. The outcome is a continuous map defined within the myocardium where not only current state-of-the-art measures of transmurality can be calculated, but also information on the location of nonviable tissue is(More)
Diffusion Tensor Magnetic Resonance Imaging (DTI) is a rather new technique that allows in vivo imaging of the brain nervous structure. The DTI data is a 3D second-order positive semidefinite tensor field. DTI analysis and visualization is a challenging field due to the lack of standards and high-dimensionality of the data. This project focused on 1)(More)
In geometric active contour algorithms, a re-initialization step must be performed by the level set function to remain close to a signed distance function, in order to avoid numerical instabilities. We propose a new re-initialization method that may be employed as a standalone method to recover the signed distance condition, or may be embedded directly into(More)
Cardiovascular diseases are the leading cause of death globally. Therefore, classification tools play a major role in prevention and treatment of these diseases. Statistical learning theory applied to magnetic resonance imaging has led to the diagnosis of a variety of cardiomyopathies states. We propose a two-stage classification scheme capable of(More)
  • 1