NDLI: Quantitative evaluation of margin sharpness of pulmonary nodules in lung CT images

Content Provider	IET Digital Library
Author	Dhara, Ashis Kumar Mukhopadhyay, Sudipta Chakrabarty, Satrajit Garg, Mandeep Khandelwal, Niranjan
Abstract	Pulmonary nodules are the potential manifestation of lung cancer. Margin sharpness of a nodule is an important imaging characteristic for estimation of its malignancy. Quantitative evaluation of margin sharpness could be helpful in the development of content-based image retrieval system of pulmonary nodules and computer-aided diagnosis system for lung cancer. In this article, margin sharpness of a nodule is represented using the combination of histogram spread of averaged gradient and acutance of nodule. The novelty of the proposed method lies in the parsimony of model representing the margin sharpness. The most recent technique on the computation of margin sharpness of pulmonary nodules considers a representative slice of the nodule and it depends on manual segmentation of nodules by a trained radiologist. The authors have automated the most recent technique for comparative study. The reproducibility of the proposed technique is evaluated on reference image database to evaluate response (RIDER) coffee break data set. The performance of the proposed and competing techniques across modalities are evaluated in terms of precision, mean similarity and normalised discounted cumulative gain on 891 nodules of LIDC/IDRI public database. The proposed method outperforms the competing techniques.
Starting Page	631
Ending Page	637
Page Count	7
ISSN	17519659
Volume Number	10
e-ISSN	17519667
Issue Number	Issue 9, Sep (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/10/9
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2015.0784
Journal	IET Image Processing
Publisher Date	2016-09-01
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Biology And Medical Computing Biomedical Imaging/measurement Cancer Computer Vision And Image Processing Technique Computer-aided Diagnosis System Computerised Tomography Content-based Image Retrieval System Histogram Spread Image Retrieval Image Segmentation Information Retrieval Technique LIDC/IDRI Public Database Lung Lung Cancer Lung CT Image Malignancy Margin Sharpness Mean Similarity Medical Image Processing Nodule Segmentation Normalised Discounted Cumulative Gain Optical, Image And Video Signal Processing Patient Diagnostic Method And Instrumentation Pulmonary Nodules Radiography And Computed Tomography Radiologist Tumours X-Ray Technique X-Rays And Particle Beam
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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