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Classification Driven Semantic Based Medical Image Indexing and Retrieval
Y. Liu, F. Dellaert, and W.E. Rothfus
tech. report CMU-RI-TR-98-25, Robotics Institute, Carnegie Mellon University, 1998.

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The motivation for our work is to develop a truly semantic­based image retrieval system that can discriminate between images differing only through subtle, domain­specific cues, which is a characteristic feature of many medical images. We propose a novel image retrieval framework centered around classification driven search for a good similarity metric (image index features) based on the image semantics rather than on appearance.

Given a semantically well­defined image set, we argue that image classification and image retrieval share fundamentally the same goal. Thus, the distance metric defining a classifier which performs well on the data should be expected to behave well when used as the similarity metric for semantic image retrieval. In this paper we shall report our methodology and results on 3D grey­level medical image retrieval.

Sponsor: Allegheny­Singer Research Institute
Grant ID: NIST#70NANB5H1183

Associated centers: VASC and MRTC
Associated labs/groups: Biomedical Image Analysis, Computational Symmetry, and Medical Robotics and Computer Assisted Surgery
Associated project: A Statistical Quantification of Human Brain Asymmetry

Y. Liu, F. Dellaert, and W.E. Rothfus, Classification Driven Semantic Based Medical Image Indexing and Retrieval, tech. report CMU-RI-TR-98-25, Robotics Institute, Carnegie Mellon University, 1998.

@techreport{Liu_1998_472,
   author = "Yanxi Liu and Frank Dellaert and William E. Rothfus",
   title = "Classification Driven Semantic Based Medical Image Indexing and Retrieval",
   institution = "Robotics Institute, Carnegie Mellon University",
   year = "1998",
   number = "CMU-RI-TR-98-25",
   address = "Pittsburgh, PA"
}