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Measuring the Angle of Hallux Valgus Using Segmentation of Bones on X-Ray Images

  • 2019
  • OriginalPaper
  • Chapter
Published in:
Authors
Konrad Kwolek
Henryk Liszka
Bogdan Kwolek
Artur Gądek
Published in
Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions
Publisher
Springer International Publishing

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Abstract

Hallux valgus is a common feet problem. A hallux valgus deformity is when there is medial deviation of the first metatarsal and lateral deviation of the great toe. In this work, we introduce an algorithm for automatic recognition of hallux valgus on X-ray images with feet. The bones are segmented on the basis of U-Net convolutional neural network. The neural network has been trained on thirty manually segmented images by an orthopedist. We present both qualitative and quantitative segmentation results on ten test images. We present algorithms for great toe extraction and hallux valgus angle (HVA) estimation. The HVA is estimated as the angle between two lines fitted to big toe skeleton. We compare results that were obtained manually, by computer-assisted programs that are used by radiologists, and by the proposed algorithm.

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previous chapter Breast Cancer Classification on Histopathological Images Affected by Data Imbalance Using Active Learning and Deep Convolutional Neural Network
next chapter Human Body Posture Recognition Using Wearable Devices
Title
Measuring the Angle of Hallux Valgus Using Segmentation of Bones on X-Ray Images
Authors
Konrad Kwolek
Henryk Liszka
Bogdan Kwolek
Artur Gądek
Copyright Year
2019
Book
Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions

Print ISBN: 978-3-030-30492-8

Electronic ISBN: 978-3-030-30493-5

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-30493-5_32
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