Classification of medical images using local representations

Abstract In medical image retrieval, the images are usually subject to a large range of variability. In order to classify medical images, we therefore propose the use of local representations, which are small square windows taken from the images. This approach is combined with a fast approximate�-nearest neighbor technique and yields state-of-the-art results on a medical image database of 1617 images.

Classification of medical images using local representations

Abstract In medical image retrieval, the images are usually subject to a large range of variability. In order to classify medical images, we therefore propose the use of local representations, which are small square windows taken from the images. This approach is combined with a fast approximate ¦-nearest neighbor technique and yields state-of-the-art results on a medical image database of 1617 images.