Image languages in intelligent radiological palm diagnostics

  • Authors:

  • Marek R. Ogiela;Ryszard Tadeusiewicz;Lidia Ogiela

  • Affiliations:

  • Institute of Automatics, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059, Krakow, Poland;Institute of Automatics, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059, Krakow, Poland;Faculty of Management, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059, Krakow, Poland

  • Venue:
  • Pattern Recognition
  • Year:
  • 2006

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Abstract

This paper presents a new technique of computer-aided analysis and recognition of pathological wrist bone lesions. This method uses artificial intelligence (AI) techniques and mathematical linguistics allowing to evaluate automatically and analyse the structure of the said bones, based on palm radiological images. Possibilities of computer interpretation of selected images, based on the methodology of automatic medical image understanding, as introduced by the authors, were created owing to the introduction of an original relational description of individual palm (wrist) bones. This description has been built with the use of graph linguistic formalisms already applied in artificial intelligence. These were, however, developed and adjusted to the needs of automatic medical image understanding in earlier works of the authors, as specified in the bibliography section of this paper. The research described in this paper has demonstrated that the for needs of palm (wrist) bone diagnostics, specialist linguistic tools such as expansive graph grammars and EDT-label graphs are particularly well-suited. Defining a graph image language adjusted to the specific features of the scientific problem here-described allowed for a semantic description of correct palm bone structures (with consideration to idiosyncratic features). It also enabled interpretation of images showing some in-born lesions, such as additional bones; or acquired lesions such as their incorrect junctions resulting from injuries and synostoses.