A subpixel edge detector applied to aortic dissection detection

  • Authors:
  • A. Trujillo-Pino;K. Krissian;D. Santana-Cedrés;J. Esclarín-Monreal;J. M. Carreira-Villamor

  • Affiliations:
  • Centro de Tecnologías de la Imagen (CTIM), Universidad de Las Palmas de Gran Canaria (ULPGC), Spain;Centro de Tecnologías de la Imagen (CTIM), Universidad de Las Palmas de Gran Canaria (ULPGC), Spain;Centro de Tecnologías de la Imagen (CTIM), Universidad de Las Palmas de Gran Canaria (ULPGC), Spain;Centro de Tecnologías de la Imagen (CTIM), Universidad de Las Palmas de Gran Canaria (ULPGC), Spain;Universidad de Santiago de Compostela (USC), Spain

  • Venue:
  • EUROCAST'11 Proceedings of the 13th international conference on Computer Aided Systems Theory - Volume Part II
  • Year:
  • 2011

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Abstract

The aortic dissection is a disease that can cause a deadly situation, even with a correct treatment. It consists in a rupture of a layer of the aortic artery wall, causing a blood flow inside this rupture, called dissection. The aim of this paper is to contribute to its diagnosis, detecting the dissection edges inside the aorta. A subpixel accuracy edge detector based on the hypothesis of partial volume effect is used, where the intensity of an edge pixel is the sum of the contribution of each color weighted by its relative area inside the pixel. The method uses a floating window centred on the edge pixel and computes the edge features. The accuracy of our method is evaluated on synthetic images of different thickness and noise levels, obtaining an edge detection with a maximal mean error lower than 16 percent of a pixel.