Efficient PET-CT image retrieval using graphs embedded into a vector space

Abstract

Combined positron emission tomography and computed tomography (PET-CT) produces functional data (from PET) in relation to anatomical context (from CT) and it has made a major contribution to improved cancer diagnosis, tumour localisation, and staging. The ability to retrieve PET-CT images from large archives has potential applications in diagnosis, education, and research. PET-CT image retrieval requires the consideration of modality-specific 3D image features and spatial contextual relationships between features in both modalities. Graph-based retrieval methods have recently been applied to represent contextual relationships during PET-CT image retrieval. However, accurate methods are computationally complex, often requiring offline processing, and are unable to retrieve images at interactive rates. In this paper, we propose a method for PET-CT image retrieval using a vector space embedding of graph descriptors. Our method defines the vector space in terms of the distance between a graph representing a PET-CT image and a set of fixed-sized prototype graphs; each vector component measures the dissimilarity of the graph and a prototype. Our evaluation shows that our method is significantly faster (≈800× speedup, p <; 0.05) than retrieval using the graph-edit distance while maintaining comparable precision (5% difference, p > 0.05).