NDLI: Features Based IUGR Diagnosis Using Variational Level Set Method and Classification Using Artificial Neural Networks

Content Provider	IEEE Xplore Digital Library
Author	Gadagkar, A.V. Shreedhara, K.S.
Copyright Year	2014
Description	Author affiliation: Dept. of C.S. & E., U.B.D.T. Coll. of Eng., Davangere, India (Gadagkar, A.V.; Shreedhara, K.S.)
Abstract	Intrauterine growth restriction (IUGR) is the failure of the fetus to achieve his/her intrinsic growth potential. IUGR results in significant perinatal and long-term complications, including the development of insulin resistance/metabolic syndrome in adulthood [5]. Accurate and effective monitoring of fetal growth is one of the key component of prenatal care [3]. Ultrasound evaluation is considered the cornerstone of diagnosis and surveillance of the growth-restricted fetus [2]. Ultrasound measurements play a significant role in obstetrics as an accurate means for the estimation of the fetal age. Several parameters are used as aging parameters, the most important of which are the biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC) and femur length (FL). Serial measurement of these parameters over time is used to determine the fetal condition. Hence, consistency and reproducibility of measurements is an important issue. Consequently the automatic segmentation of anatomical structures in ultrasound imagery is a real challenge due to acoustic interferences (speckle noise) and artifacts which are inherent in these images. In this paper, a novel method is proposed for developing a Computer Aided Diagnosis (CAD) system for diagnosis and classification of IUGR foetuses. Diagnosis is performed by segmenting and extracting the required foetus features from an ultrasound image, using the Re-initialization free level set with Reaction Diffusion (RD) technique. An artificial neural network (ANN) classifier is developed, the features extracted are provided to the designed ANN model. The ANN then classifies normal and abnormal fetuses based on features provided.
Starting Page	303
Ending Page	309
File Size	379343
Page Count	7
File Format	PDF
ISBN	9780769551005
DOI	10.1109/ICSIP.2014.54
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-08
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Reaction Diffusion Ultrasonic imaging Ultrasonic variables measurement Level set Artificial Neural Network Artificial neural networks Feature extraction Fetus Mathematical model Ultrasound Equations
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

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