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DC Field | Value | Language |
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dc.contributor.author | Simu, S. | - |
dc.contributor.author | Lal, S. | - |
dc.contributor.author | Fadte, K. | - |
dc.contributor.author | Harlapur, A. | - |
dc.date.accessioned | 2020-03-31T08:31:13Z | - |
dc.date.available | 2020-03-31T08:31:13Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization, 2019, Vol.7, 1, pp.59-87 | en_US |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/11367 | - |
dc.description.abstract | Segmentation of bones from hand radiograph is an important step in automated bone age assessment (ABAA) system. Main challenges in the segmentation of bones are the intensity inhomogeneity caused by the irregular distribution of X-rays and the overlapping pixel intensities between the bone and soft tissue. Hence, there is a need to develop a robust segmentation technique to tackle the problems associated with the hand radiographs. This paper proposes a fully automatic technique for segmentation of phalanges from left-hand radiograph for bone age assessment. The proposed technique is divided into five stages which are pre-processing, extraction of Phalangeal region of interest, edge preservation, segmentation of phalanges and post-processing. Quantitative and qualitative results of proposed segmentation technique are evaluated and compared with other state-of-the-art segmentation methods. Qualitative results of proposed segmentation technique are also validated by different medical experts. The segmentation accuracy achieved by proposed segmentation technique is 94%. The proposed technique can be used for development of fully ABAA of a person for better accuracy. 2017, 2017 Informa UK Limited, trading as Taylor & Francis Group. | en_US |
dc.title | Fully automatic segmentation of phalanges from hand radiographs for bone age assessment | en_US |
dc.type | Article | en_US |
Appears in Collections: | 1. Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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16 Fully automatic segmentation.pdf | 8.62 MB | Adobe PDF | View/Open |
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