Paper Info
Title
Content Based Image Retrieval In Digital Pathology Using Speeded Up Robust Features
Abstract
The recent expand in the utilization of Whole Slide scanners in Digital Pathology gave birth to a production of massive amount of data and the need of integration of Digital Pathology Systems (DPS's) into modern Laboratory Information Systems (LIS's). In this context, the problem of automatically retrieving a particular image from a large set of digital images that contains similar medical visual content has gained fruitful ground. This work investigates the fast and consistent properties of the Speeded-Up Robust Features (SURF) algorithm in order to search in the content of a digital pathology image, detect and find similarities for content-based image retrieval. An important aspect of this work is the diversity of Whole Slide Scanners. The proposed methodology that involves the process of the comparison of digital pathology images, mostly WSI, with the use of the SURF algorithm was proved robust to various condition changes.
Year
DOI
Venue
2018
10.1007/978-3-319-92007-8_32
ARTIFICIAL INTELLIGENCE APPLICATIONS AND INNOVATIONS, AIAI 2018
Keywords
Field
DocType
Digital pathology, Laboratory information system, Content based image retrieval (CBIR), Speeded Up Robust Features (SURF), Whole Slide Imaging (WSI)
Information system,Pattern recognition,Computer science,Image retrieval,Digital pathology,Digital image,Artificial intelligence,Content-based image retrieval
Conference
Volume
ISSN
Citations 
519
1868-4238
0
PageRank 
References 
Authors
0.34
2
2
Name
Order
Citations
PageRank
A. Kallipolitis100.34
Ilias Maglogiannis293797.72