• Corpus ID: 16367178

T Ri I I Tru

@inproceedings{Chu2004TRI,
  title={T Ri I I Tru},
  author={Wesley W. Chu and Chih-Cheng Hsu and Alfonso F. Cardenas and Ricky K. Taira},
  year={2004}
}
A knowledge-based approach to retrieve medical images by feature and content with spatial and temporal constructsk developed. Selected objects of interest in a medical image (e.g., x-ray, MR image) are segmented, and contours are generated from these objects. Features (e.g., shape, size, texture) and content (e.g., spatial relationships among objects) are extracted and stored in a feature and content database. Knowledge about image features can be expressed as a hierarchical structure called a… 

References

SHOWING 1-10 OF 40 REFERENCES
A Knowledge-Based Approach for Retrieving Images by Content
A knowledge based approach is introduced for retrieving images by content. It supports the answering of conceptual image queries involving similar-to predicates, spatial semantic operators, and
QBIC project: querying images by content, using color, texture, and shape
TLDR
The main algorithms for color texture, shape and sketch query that are presented, show example query results, and discuss future directions are presented.
A semantic modeling approach for image retrieval by content
TLDR
A semantic data model is introduced to capture the hierarchical, spatial, temporal, and evolutionary semantics of images in pictorial databases, and a spatial evolutionary query language (SEQL) is presented, which provides direct image object manipulation capabilities.
The Knowledge-Based Object-Oriented PICQUERY+ Language
TLDR
The PICQUERY/sup +/ language and its underlying stacked image data model are enhanced with major advances that include convenient specification of the data domain space among a multimedia database federation, visualization of underlying data models, knowledge-based hierarchies, and domain rules.
A Visual Information Management System for the Interactive Retrieval of Faces
TLDR
A general architecture for visual information-management systems (VIMS), which combine the strengths of both approaches, is presented, and a VIMS developed for face-image retrieval is presented to demonstrate these ideas.
An error-based conceptual clustering method for providing approximate query answers
TLDR
A conceptual clustering method is proposed for discovering high level concepts of numerical attribute values from databases that considers both frequency and value distributions of data to partition the data set of one or more attributes into clusters that minimize the relaxation error.
Object-oriented conceptual modeling of video data
TLDR
A graphical data model for specifying spatio-temporal semantics of video data that segments a video clip into subsegments consisting of objects so that a user can create his/her own, object-oriented view of the video database.
Automatic segmentation of bones from digital hand radiographs
TLDR
A robust and accurate method that automatically segments phalangeal and epiphyseal bones from digital pediatric hand radiographs exhibiting various stages of growth can be applied toward areas such as the determination of bone age, the development of a normal hand atlas, and the characterization of many congenital and acquired growth diseases.
Unified Data Model for Representing Multimedia, Timeline, and Simulation Data
TLDR
A unified data model that represents multimedia, timeline, and simulation data utilizing a single set of related data modeling constructs is described, giving multimedia schemas and queries a degree of data independence even for these complex data types.
...
1
2
3
4
...