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- W2082057148 abstract "ABSTRACT Content-based image retrieval has been applied to many different biomedical applications 1 . In almost all cases, retrievals involve a single query image of a particular modality and retrieved images are from this same modality. For example, one system may retrieve color images from eye exams, while another retrieves fMRI images of the brain. Yet real patients often have had tests from multiple different modalities, and retrievals based on more than one modality could provide information that single modality searches fail to see. In this paper, we show medical image retrieval for two different single modalities and propose a model for multimodal fusion that will lead to improved capabilities for physicians and biomedical researchers. We describe a graphical user interface for multimodal retrieval that is being tested by real biomedical researchers in several different fields. Keywords: content-based retrieval, multimodality data, biomedical imaging, fusion 1. INTRODUCTION The term CBIR (content-based image retrieval) designates the retrieval of images based on their visual similarity to a user-supplied query image or to a set of user-specified image features. CBIR has been, and can be widely used in many areas, such as photograph archives, medical diagnosis, the military, retail catalogs, and remote sensing systems. Common methods for extracting content from images usually make use of color, texture and shape features. There are many CBIR systems that have been developed for use in industry, such as the IBM QBIC system" @default.
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- W2082057148 date "2009-01-18" @default.
- W2082057148 modified "2023-09-23" @default.
- W2082057148 title "A model of multimodal fusion for medical applications" @default.
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- W2082057148 doi "https://doi.org/10.1117/12.805490" @default.
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