Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Pradeepkumar, G.a; * | Kavitha, S.b
Affiliations: [a] Department of ECE, KPR Institute of Engineering and Technology, Coimbatore, Tamil Nadu, India | [b] Department of ECE, Nandha Engineering College, Erode, Tamil Nadu, India
Correspondence: [*] Corresponding author. G. Pradeepkumar, Assistant Professor, Department of ECE, KPR Institute of Engineering and Technology, Coimbatore-641407, Arasur, Uthupalayam, Tamil Nadu, India. E-mail: [email protected].
Abstract: To provide the best possible performance in precisely segmenting clinical images, several approaches are used. Convolutional neural networks are one method used in it to extract its features, which combine several models with several additional methods. It also improves the efficiency of generalisation between categorised and uncategorized image categories. The method proposed combines multi-style image fusion with two-dimensional fracture image representation. The photographs on this page have been updated with a variety of images to improve concentration sharing and achieve the desired visual look. The border detection algorithm is then used to extract the exact border of the image from the contrast extended images. It will then be divided into basic and comprehensive layers. The fused image was then created using augmented end layers.
Keywords: Segmenting, clinical images, extract features, categorized image, uncategorized image, multi style, border detection, image extraction
DOI: 10.3233/JIFS-239695
Journal: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2024
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]