Set of methods for spontaneous ICH segmentation and tracking from CT head images

  • Authors:

  • Noel Pérez;José A. Valdés;Miguel A. Guevara;Luis A. Rodríguez;J. M. Molina

  • Affiliations:

  • Center for Advanced Computer Sciences Technologies, Ciego de Ávila University, Ciego de Ávila, Cuba;Center for Advanced Computer Sciences Technologies, Ciego de Ávila University, Ciego de Ávila, Cuba;Center for Advanced Computer Sciences Technologies, Ciego de Ávila University, Ciego de Ávila, Cuba;Intensive Care Unit, Morón Hospital, Ciego de Ávila, Cuba;Center for Advanced Computer Sciences Technologies, Ciego de Ávila University, Ciego de Ávila, Cuba

  • Venue:
  • CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
  • Year:
  • 2007

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Abstract

Spontaneous intracerebral hemorrhage (ICH) is a common cause of stroke, due to this; the early evolution and quantitative analysis of the ICH is important for the treatment and the course of patient's recovery. Computer-based diagnosis systems have played an important role in quantitative analysis of medical images aiding medical personnel in selecting the appropriated treatment of diseases. This paper outlines a set of three methods for ICH segmentation and tracking from computer tomography (CT) head images, based on a suitable combination of digital image processing and pattern recognition techniques. Two of these methods are carried out in a semiautomatic way and the other one is performed in a manual way. Methods developed were tested successfully by medical researchers in a representative dataset of CT head images (patient studies).