|The motivation for our work is to develop a truly semantic?ased image retrieval system that can discriminate between images differing only through subtle, domain?pecific 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 well?efined 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 grey?evel medical image retrieval.
Sponsor: Allegheny?inger Research Institute
Grant ID: NIST#70NANB5H1183
Associated Center(s) / Consortia: Vision and Autonomous Systems Center and Medical Robotics Technology Center
Associated Lab(s) / Group(s): Medical Robotics and Computer Assisted Surgery, Computational Symmetry, Biomedical Image Analysis
Associated Project(s): A Statistical Quantification of Human Brain Asymmetry
|Yanxi Liu, Frank Dellaert, and William E. Rothfus, "Classification Driven Semantic Based Medical Image Indexing and Retrieval," tech. report CMU-RI-TR-98-25, Robotics Institute, Carnegie Mellon University, 1998|
author = "Yanxi Liu and Frank Dellaert and William E. Rothfus",
title = "Classification Driven Semantic Based Medical Image Indexing and Retrieval",
booktitle = "",
institution = "Robotics Institute",
year = "1998",
address= "Pittsburgh, PA",
|The Robotics Institute is part of the School of Computer Science, Carnegie Mellon University.|
Contact Us | Update Instructions