There is a growing need for the ability to query image databases based on similarity of image content rather than strict keyword search. As distance computations can be expensive, there is a need for indexing systems and algorithms that can eliminate candidate images without performing distance calc
ASSERT: A Physician-in-the-Loop Content-Based Retrieval System for HRCT Image Databases
โ Scribed by Chi-Ren Shyu; Carla E. Brodley; Avinash C. Kak; Akio Kosaka; Alex M. Aisen; Lynn S. Broderick
- Publisher
- Elsevier Science
- Year
- 1999
- Tongue
- English
- Weight
- 574 KB
- Volume
- 75
- Category
- Article
- ISSN
- 1077-3142
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โฆ Synopsis
It is now recognized in many domains that content-based image retrieval from a database of images cannot be carried out by using completely automated approaches. One such domain is medical radiology for which the clinically useful information in an image typically consists of gray level variations in highly localized regions of the image. Currently, it is not possible to extract these regions by automatic image segmentation techniques. To address this problem, we have implemented a human-in-the-loop (a physician-inthe-loop, more specifically) approach in which the human delineates the pathology bearing regions (PBR) and a set of anatomical landmarks in the image when the image is entered into the database. To the regions thus marked, our approach applies low-level computer vision and image processing algorithms to extract attributes related to the variations in gray scale, texture, shape, etc. In addition, the system records attributes that capture relational information such as the position of a PBR with respect to certain anatomical landmarks. An overall multidimensional index is assigned to each image based on these attribute values.
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