Three-dimensional Content-Based Cardiac Image Retrieval using global and local descriptors.

The increase in volume of medical images generated and stored has created difficulties in accurate image retrieval. An alternative is to generate three-dimensional (3D) models from such medical images and use them in the search. Some of the main cardiac illnesses, such as Congestive Heart Failure (CHF), have deformation in the heart's shape as one of the main symptoms, which can be identified faster in a 3D object than in slices. This article presents techniques developed to retrieve 3D cardiac models using global and local descriptors within a content-based image retrieval system. These techniques were applied in pre-classified 3D models with and without the CHF disease and they were evaluated by using Precision vs. Recall metric. We observed that local descriptors achieved better results than a global descriptor, reaching 85% of accuracy. The results confirmed the potential of using 3D models retrieval in the medical context to aid in the diagnosis.

Applying Distance Histogram to retrieve 3D cardiac medical models.

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.