Fully automatic segmentation of phalanges from hand radiographs for bone age assessment

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2019

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Taylor and Francis Ltd.

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.

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Keywords

Bone, Image segmentation, Automatic segmentations, Bone age assessment, Bone segmentation, Hand bone segmentation, Hand bones, Level-set function, Phalangeal region of interest, Region-of-interest, Regions of interest, Segmentation techniques, Radiography, anisotropy, Article, artificial intelligence, bone age, bone age determination, bone development, computer aided design, ferritin blood level, fuzzy system, hand bone, hand radiography, histogram, human, image segmentation, machine learning, mathematical analysis, mathematical model, medical expert, motivation, optic disk, phalanx, priority journal, reliability, support vector machine, visual field

Citation

Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization, 2019, 7, 1, pp. 59-87

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