NDLI: Segmentation and detection of Squamous cell lung malignanncy from sputum images

Content Provider	IEEE Xplore Digital Library
Author	Cherian, A. Leio, A.V. Jeeva, J.B.
Copyright Year	2015
Description	Author affiliation: Div. of Biomed. Eng., VIT Univ., Vellore, India (Cherian, A.; Leio, A.V.; Jeeva, J.B.)
Abstract	Squamous cell carcinoma (SCC) of the lungs is one of the types of non-small cell lung malignancy. Non-small cell lung cancers accounts for about 80% of lung cancers, and of these, roughly 30% are SCC's, which are mostly seen in smokers. SCC is seen in the tissue that lines the air passages in the lungs. The work is based on the Segmentation and Detection of Squamous cell carcinoma of lung from sputum images based on cytopatholgical characteristics of the cell. These images are acquired by the digital microscope with specified magnification. This process requires the detection of the Squamous cell in the sputum images characterized by the hyper chromatic cell region and the change in the nucleus angulations and its irregularities of the cells. In this method color segmentation of the cells is followed by its filtering and nucleus segmentation is performed. Using these parameters classification of the cell is done.
Starting Page	34
Ending Page	37
File Size	359575
Page Count	4
File Format	PDF
e-ISBN	9781479972258
DOI	10.1109/ECS.2015.7124920
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-02-26
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Nucleus angulations Image segmentation Squamous cell carcinoma Image color analysis Filtering Shape Lungs Conferences Sputum Color segmentation Cancer
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

Cell extraction from sputum images for early lung cancer detection

Morphology analysis of sputum color images for early lung cancer diagnosis

Extraction of sputum cells using thresholding techniques for lung cancer detection

Detection and segmentation of sputum cell for early lung cancer detection

Early detection of lung cancer based on sputum color image analysis

Identification of Lung Cancer Based on Shape and Color

Segmentation of sputum color image for lung cancer diagnosis based on mean shift algorithm

A comparison of cluster distance metrics for the segmentation of sputum color image using unsupervised hopfield neural network classifier

Segmentation of sputum color image for lung cancer diagnosis

Segmentation and detection of Squamous cell lung malignanncy from sputum images

Similar Documents

Cell extraction from sputum images for early lung cancer detection

Morphology analysis of sputum color images for early lung cancer diagnosis

Extraction of sputum cells using thresholding techniques for lung cancer detection

Detection and segmentation of sputum cell for early lung cancer detection

Early detection of lung cancer based on sputum color image analysis

Identification of Lung Cancer Based on Shape and Color

Segmentation of sputum color image for lung cancer diagnosis based on mean shift algorithm

A comparison of cluster distance metrics for the segmentation of sputum color image using unsupervised hopfield neural network classifier

Segmentation of sputum color image for lung cancer diagnosis

Segmentation and detection of Squamous cell lung malignanncy from sputum images