Three-dimensional models are being extensively used in the medical area in order to improve clinical medical examinations and diagnosis. The Cardiology field handles with several types of image slices to compose the diagnosis. MRI (Magnetic Resonance Imaging) is a non-invasive technique to detect anomalies from internal images of the human body that generates hundreds of images, which takes long for the specialist to analyze frame by frame and the diagnosis precision can be affected. Many cardiac diseases could be identified through shape deformation, but systems aimed to aid diagnosis usually identify shapes in two-dimensional (2D) images. Our aim is to apply a shape descriptor to retrieve three-dimensional cardiac models, obtained from a set of 2D slices, which were segmented and reconstructed from MRI images using their geometry information. Preliminary results show that the shape deformation in 3D models can be a good indicator to detect Congestive Heart Failure, a very common heart disease.
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