ASSERT: A Physician-in-the-Loop Content-Based Retrieval System for HRCT Image Databases

1999 ◽  
Vol 75 (1-2) ◽  
pp. 111-132 ◽  
Author(s):  
Chi-Ren Shyu ◽  
Carla E. Brodley ◽  
Avinash C. Kak ◽  
Akio Kosaka ◽  
Alex M. Aisen ◽  
...  
2001 ◽  
Author(s):  
Chi-Ren Shyu ◽  
Seth A. Havermann ◽  
Kristopher Stice ◽  
Georgia Davis

2014 ◽  
Vol 573 ◽  
pp. 529-536
Author(s):  
T. Kanimozhi ◽  
K. Latha

Image retrieval system becoming a more popular in all the disciplines of image search. In real-time, interactive image retrieval system has become more accurate, fast and scalable to large collection of image databases. This paper presents a unique method for an image retrieval system based on firefly algorithm, which improve the accuracy and computation time of the image retrieval system. The firefly algorithm is utilized to optimize the image retrieval process via search for nearly optimal combinations between the corresponding features as well as finding out approximate optimized weights for similarities with respect to the features. The proposed method is able to dynamically reflect the user’s intention in the retrieval process by optimizing the objective function. The Efficiency of the proposed method is compared with other existing image retrieval methods through precision and recall. The performance of the method is experimented on the Corel and Caltech database images.


Author(s):  
Ringo W. K. Lam ◽  
Kent K. T. Cheung ◽  
Horace H. S. Ip ◽  
Lilian H. Y. Tang ◽  
R. Hanka

Author(s):  
Yung-Kuan Chan ◽  
Chin-Chen Chang

Because of the demand for efficient management in images, much attention has been paid to image retrieval over the past few years. The text-based image retrieval system is commonly used in traditional search engines (Ratha et al., 1996), where a query is represented by keywords that are usually identified and classified by human beings. Since people have different understandings on a particular image, the consistency is difficult to maintain. When the database is larger, it is arduous to describe and classify the images because most images are complicated and have many different objects. There has been a trend towards developing the content-based retrieval system, which tries to retrieve images directly and automatically based on their visual contents.


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