NDLI: An Iterative Thresholding Method for Epiphysis ROI Segmentation for Radiographic Images

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An Iterative Thresholding Method for Epiphysis ROI Segmentation for Radiographic Images

Content Provider	ACM Digital Library
Author	Agarwal, Suneeta Rajitha, B.
Abstract	Radiographic images play a vital role in identifying the Bone age of a live or dead human. Bone age is estimated using the epiphysis and carpal bones of hand x-ray. To achieve age estimation correctly the separation of bone pixels and soft tissue pixels in the ROI image is mandatory. The existing approaches like sobel, canny, clustering, region growing, watershed can be applied, but they need proper pre processing and correct initial seed point estimation to identify the edges uniquely. Therefore this paper proposes a Bone Pixel Enhancement (BPE) method, first to enhance the bone pixels by applying normal distribution to distinguishing the bone, soft tissue and background pixels. Thereafter an iterative threshold method is applied for suppressing the soft tissue pixels and background pixels. The proposed approach doesn't need any initial seed point to be chosen. Performance is compared with sobel, canny, adaptive means, region growing and watershed by evaluating the metrics Precision, Recall, Specificity, F-measure, Error rate and Accuracy. Proposed algorithm had success rate same as clustering with right center estimate. Here 97% accuracy in average is achieved by considering 50 images.
Starting Page	1
Ending Page	7
Page Count	7
File Format	PDF
ISBN	9781450334419
DOI	10.1145/2743065.2743081
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-03-06
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Image segmentation Histogram Accuracy Specificity X-ray images Precision Error rate Recall Clustering Image texture analysis Iterative threshold F-measure
Content Type	Text
Resource Type	Article

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