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Hand Pose Estimation for Pediatric Bone Age Assessment

  • María EscobarEmail author
  • Cristina González
  • Felipe Torres
  • Laura Daza
  • Gustavo Triana
  • Pablo Arbeláez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11769)

Abstract

We present a new experimental framework for the task of Bone Age Assessment (BAA) based on a local analysis of anatomical Regions Of Interest (ROIs) of hand radiographs. For this purpose, we introduce the Radiological Hand Pose Estimation (RHPE) Dataset, composed of 6,288 hand radiographs from a population that is different from the currently available BAA datasets. We provide Bone Age groundtruths annotated by two expert radiologists as well as bounding boxes and keypoints denoting anatomical ROIs annotated by multiple trained subjects. In addition to RHPE, we provide bounding boxes and ROIs annotations for the publicly available BAA dataset by the Radiological Society of North America (RSNA) [9]. We propose a new experimental framework with hand detection and hand pose estimation as new tasks to extract local information for BAA methods. Thanks to its fine-grained and precisely localized annotations, our dataset will allow to exploit local information to push forward automated BAA algorithms. Additionally, we conduct experiments with state-of-the-art methods in each of the new tasks. Our proposed model, named BoNet, leverages local information and significantly outperforms state-of-the-art methods in BAA. We provide the RHPE dataset with the corresponding annotations, as well as the trained models, the source code for BoNet and the additional annotations created for the RSNA dataset.

Keywords

Bone Age Assessment Computer aided diagnosis Hand radiograph Regions Of Interest 

Notes

Acknowledgments

This project was partially funded by Colciencias grant 841-2017. The authors thank Edgar Margffoy-Tuay for his support in developing the annotation server and the students of IBIO-3470 at Uniandes for their help as annotators.

Supplementary material

490281_1_En_59_MOESM1_ESM.pdf (592 kb)
Supplementary material 1 (pdf 591 KB)

Supplementary material 2 (mp4 14995 KB)

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • María Escobar
    • 1
    Email author
  • Cristina González
    • 1
  • Felipe Torres
    • 1
  • Laura Daza
    • 1
  • Gustavo Triana
    • 2
  • Pablo Arbeláez
    • 1
  1. 1.Universidad de los AndesBogotáColombia
  2. 2.Fundación Santa Fe de BogotáBogotáColombia

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