Model-based recognition of anatomical objects from medical images

We present both a high-level symbolic model of the human brain, and a method of using this model to aid in the recognition of objects from medical images. The model is stored as a frame-based semantic network consisting of three coexisting graphs (a spatial adjacency graph, a part hierarchy and an i...

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Veröffentlicht in:	Image and vision computing 1994, Vol.12 (8), p.499-507
Hauptverfasser:	Robinson, GP, Colchester, ACF, Griffin, LD
Format:	Artikel
Sprache:	eng
Schlagworte:	Applied sciences Artificial intelligence Computer science control theory systems Exact sciences and technology medical image interpretation object centred Pattern recognition. Digital image processing. Computational geometry representation
Online-Zugang:	Volltext
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Beschreibung
Zusammenfassung:	We present both a high-level symbolic model of the human brain, and a method of using this model to aid in the recognition of objects from medical images. The model is stored as a frame-based semantic network consisting of three coexisting graphs (a spatial adjacency graph, a part hierarchy and an inheritance graph). We propose a method similar to assumption-based truth maintenance systems for the collating and reasoning processes required in the labelling of input images.
ISSN:	0262-8856 1872-8138
DOI:	10.1016/0262-8856(94)90003-5