scholarly journals BIOMEDICAL IMAGE SEARCH AND RETRIEVAL ALGORITHMS

2014 ◽  
pp. 108-113
Author(s):  
O. Berezsky ◽  
G. Melnyk ◽  
Yu. Batko
Keyword(s):  
Image Features ◽  
Tumour Cells ◽  
Image Search ◽  
Biomedical Image ◽  
Colour Image ◽  
Retrieval Algorithms ◽  
Search And Retrieval

In this paper algorithm for search the tumour cells images in a database is developed. This algorithm based on shape and colour image features.

scholarly journals Remote Network Monitoring Technology Based on Computer Technology

2022 ◽  
Vol 2146 (1) ◽  
pp. 012040
Author(s):  
Huaben Wang
Keyword(s):  
Rapid Development ◽  
Image Data ◽  
Image Features ◽  
Color Histogram ◽  
Internet Technology ◽  
Image Search ◽  
Chi Square ◽  
Query Image ◽  
Data Set ◽  
Color Distribution

Abstract With the rapid development of Internet technology, using images to express the characteristics of things more direct, compared with text, audio, image expression content is more ambiguous, which makes the rapid increase of digital images on the Internet. Nowadays one of the hot directions of computer vision research is how to accurately and quickly retrieve the target image from a large amount of image data. This paper summarizes the development of image retrieval technology at home and abroad, and proposes an image search method based on color histogram and Chi-square distance. This paper discusses how to construct an image search system, which can search the image quickly, describe the color distribution of the photo with color histogram, divide the image into five regions, extract image features from the color histogram of each region, and then get the data set of multi-dimensional image features. Then the chi-square distance is used to calculate the similarity of color histogram, and the closest image is selected as the first similar image, which realizes the necessary logic of receiving query image and returning related results.

Context-Aware Medical Image Retrieval for Improved Dementia Diagnosis

2013 ◽  
pp. 434-448 ◽  
Author(s):  
Melih Soydemir ◽  
Devrim Unay
Keyword(s):  
Image Features ◽  
Added Value ◽  
Image Search ◽  
Contextual Knowledge ◽  
Dementia Diagnosis ◽  
Search Results ◽  
Diagnostic Decision ◽  
Increasing Demand ◽  
Multiple Patients ◽  
Content Information

Progress in medical imaging technology together with the increasing demand for confirming a diagnostic decision with objective, repeatable, and reliable measures for improved healthcare have multiplied the number of digital medical images that need to be processed, stored, managed, and searched. Comparison of multiple patients, their pathologies, and progresses by using image search systems may largely contribute to improved diagnosis and education of medical students and residents. Supporting image content information with contextual knowledge will lead to increased reliability, robustness, and accuracy in search results. To this end, the authors present an image search system that permits search by a multitude of image features (content), and demographics, patient’s medical history, clinical data, and ontologies (context). Moreover, they validate the system’s added value in dementia diagnosis via evaluations on publicly available image databases.

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