NDLI: A Pilot Study on Image Analysis Techniques for Extracting Early Uterine Cervix Cancer Cell Features

Content Provider	Springer Nature Link
Author	Sokouti, Babak Haghipour, Siamak Tabrizi, Ali Dastranj
Copyright Year	2011
Abstract	The second most common and preventable form of cancer among women worldwide is cervical cancer in which the signs for this disease can be detected in the early Pap smear screening of cervical cells. To improve the efficiency of expert diagnosis, we will need to automate the feature extraction of cervical cancer cells by the means of image processing techniques. This article employs image processing techniques to get the special features of normal, precancerous and cancerous cell images. We extract spectral features for cervical cancer cell detection. This article uses the noise decrease filters, OTSU threshold to make it ready for processing through 2-D Fourier and logarithmic transforms. By drawing the linear plot, we will be able to extract the feature of normal, precancerous and cancerous cells according to the texture and morphology automatically. These linear plots will be unique which can separate the cells in three groups of normal, precancerous and cancerous cells. This separation is done with 100% accuracy due to the unique linear plots. The experiment shows that extracted unique features for each cell will provide evidences for diagnoses even in cytopathology images in which the nucleus and cytoplasm segmentation algorithms suffer from complex overlaying cells.
Starting Page	1901
Ending Page	1907
Page Count	7
File Format	PDF
ISSN	01485598
Journal	Journal of Medical Systems
Volume Number	36
Issue Number	3
e-ISSN	1573689X
Language	English
Publisher	Springer US
Publisher Date	2011-01-11
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Cytopathological cell images Pap smear Cervical cancer Medical image analysis Health Informatics Statistics for Life Sciences, Medicine, Health Sciences
Content Type	Text
Resource Type	Article
Subject	Health Information Management Information Systems Health Informatics

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

Hyperchromasia and texture as effective features for analysis of malignancy in pap smear images.

Cervix Cancer Diagnosis from Pap Smear Images Using Structure Based Segmentation and Shape Analysis

Cervix Cancer Diagnosis from Pap Smear Images Using Structure Based Segmentation and Shape Analysis

Pseudo Color Features Extraction technique for cervical cancer of Pap smear images

Deep Convolution Neural Network for Malignancy Detection and Classification in Microscopic Uterine Cervix Cell Images.

An Automated Method for Segmentation of Epithelial Cervical Cells in Images of ThinPrep

Overlapping cells separation method for cervical cell images

Evaluation of the cervical cancer screening programme in Mexico: a population-based case-control study.

Segmentation of stretched pap smear cytology images using clustering algorithm.

A Pilot Study on Image Analysis Techniques for Extracting Early Uterine Cervix Cancer Cell Features

Similar Documents

Hyperchromasia and texture as effective features for analysis of malignancy in pap smear images.

Cervix Cancer Diagnosis from Pap Smear Images Using Structure Based Segmentation and Shape Analysis

Cervix Cancer Diagnosis from Pap Smear Images Using Structure Based Segmentation and Shape Analysis

Pseudo Color Features Extraction technique for cervical cancer of Pap smear images

Deep Convolution Neural Network for Malignancy Detection and Classification in Microscopic Uterine Cervix Cell Images.

An Automated Method for Segmentation of Epithelial Cervical Cells in Images of ThinPrep

Overlapping cells separation method for cervical cell images

Evaluation of the cervical cancer screening programme in Mexico: a population-based case-control study.

Segmentation of stretched pap smear cytology images using clustering algorithm.

A Pilot Study on Image Analysis Techniques for Extracting Early Uterine Cervix Cancer Cell Features