NDLI: Unsupervised segmentation of cell nuclei in cervical smear images using active contour with adaptive local region fitting energy modelling

Content Provider	IEEE Xplore Digital Library
Author	Zeng, Ziming Chen, Siping Tang, Sheng Yin, Lidong
Copyright Year	2015
Description	Author affiliation: National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Shenzhen, China (Zeng, Ziming; Chen, Siping) \|\| Shenzhen Microprofit Electronic Co., Ltd, Shenzhen, China (Tang, Sheng; Yin, Lidong)
Abstract	In this paper, we propose a method based on an adaptive active contour modelling to segment the cell nuclei from cervical smear images. The basic idea of our method is to make a contour to adaptively deform so as to get a minimized given region energy function. In order to make the evolution of the contour rely less on the intensity homogeneity and achieve the purpose of adaptive segmentation of the cell nuclei, the proposed method utilizes the morphology method to initialize the active contour modelling. Then a Gaussian kernel function is used to extract the local region and defines its local region fitting energy function which approximates the image intensities on the two sides of the contour in the local region. Finally, the Split Bregman method is used to obtain a robust numerical solution and to generate the segmentation results. In our experiments, the proposed approach can obtain accurate segmentation results compared with some state-of-the-art approaches.
Starting Page	250
Ending Page	254
File Size	316375
Page Count	5
File Format	PDF
e-ISBN	9781509000227
DOI	10.1109/BMEI.2015.7401510
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Adaptation models Image edge detection Fitting Morphology Kernel Active contours
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Active contour using local region-scalable force with expandable kernel

Segmentation of cervical cancer images using active contour models

Automatic 3D segmentation of CT images based on active contour models

Directional local region-scalable active contour using expandable kernel

An improved local distribution fitting model

Nonparametric MDL segmentation of inhomogeneous images based on Quadratic Local Binary Fitting

A novel edge detection approach on active contour for tumor segmentation

Automatic shadow detection in intra vascular ultrasound images using adaptive thresholding

A computational efficient external energy for active contour segmentation using edge propagation

Unsupervised segmentation of cell nuclei in cervical smear images using active contour with adaptive local region fitting energy modelling

Similar Documents

Active contour using local region-scalable force with expandable kernel

Segmentation of cervical cancer images using active contour models

Automatic 3D segmentation of CT images based on active contour models

Directional local region-scalable active contour using expandable kernel

An improved local distribution fitting model

Nonparametric MDL segmentation of inhomogeneous images based on Quadratic Local Binary Fitting

A novel edge detection approach on active contour for tumor segmentation

Automatic shadow detection in intra vascular ultrasound images using adaptive thresholding

A computational efficient external energy for active contour segmentation using edge propagation

Unsupervised segmentation of cell nuclei in cervical smear images using active contour with adaptive local region fitting energy modelling