NDLI: Medical image blob detection with feature stability and KNN classification

Content Provider	IEEE Xplore Digital Library
Author	Inthajak, K. Duanggate, C. Uyyanonvara, B. Makhanov, S.S. Barman, S.
Copyright Year	2011
Description	Author affiliation: Faculty of Computing, Information Systems and Mathematics, Kingston University, Penrhyn Road, Kingston upon Thames, Surrey, KTI 2EE, UK (Barman, S.) \|\| Department of Information, Computer and Communication Technology, Sirindhorn International Institute of Technology (SIIT), Thammasat University, Pathumthani, Thailand (Inthajak, K.; Duanggate, C.; Uyyanonvara, B.; Makhanov, S.S.)
Abstract	Object detection methods with feature stability along with the use of KNN algorithm are proposed within this paper. A scale-space tree is constructed based on the blobs that were created from a series of images after blurring. Features and spatial information provides the role in scalespace tree construction. After the process of blob extraction, users determine the type of blobs that were detected within the image by distinguishing classes to create ground truth images. Within the same process, KNN algorithm is applied to distinguish classes of the image's blob to demonstrate its performance.
Starting Page	128
Ending Page	131
File Size	796689
Page Count	4
File Format	PDF
ISBN	9781457706868
e-ISBN	9781457706875
DOI	10.1109/JCSSE.2011.5930107
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-05-11
Publisher Place	Thailand
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Scale-space K Nearest Neighbor Object detection Feature stability
Content Type	Text
Resource Type	Article

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