A deep learning approach to automatically quantify lower extremity alignment in children.

Journal: Skeletal radiology
PMID: 34254170

Abstract

OBJECTIVE: To develop and validate a convolutional neural network (CNN) capable of predicting the anatomical landmarks used to calculate the hip-knee-ankle angles (HKAAs) from radiographs and thereby quantify lower extremity alignments in children.

Authors

  • Andy Tsai
    Department of Radiology, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA. andy.tsai@childrens.harvard.edu.

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