Automation of clinical measurements on radiographs of children's hips

Peter Thompson, Medical Annotation Collaborative, Daniel C Perry, Timothy Cootes, Claudia Lindner

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

129 Downloads (Pure)


Developmental dysplasia of the hip (DDH) and cerebral palsy (CP) related hip migration are two of the most common orthopaedic diseases in children, each affecting around 1-2 in 1000 children. For both of these conditions, early detection is a key factor in long term outcomes for patients. However, early signs of the disease are often missed and manual monitoring of routinely collected radiographs is time-consuming and susceptible to inconsistent measurement. We propose an automatic system for calculating acetabular index (AcI) and Reimer's migration percentage (RMP) from paediatric hip radiographs. The system applies Random Forest regression-voting to fully automatically locate the landmark points necessary for the calculation of the clinical metrics. We show that the fully automatically obtained AcI and RMP measurements are in agreement with manual measurements obtained by clinical experts, and have replicated these findings in a clinical dataset. Such a system allows for the reliable and consistent monitoring of DDH and CP patients, aiming to improve patient outcomes through hip surveillance programmes.
Original languageEnglish
Title of host publicationSpringer Lecture Notes in Computer Science
EditorsLinwei Wang, Qi Dou, P. Thomas Fletcher, Stefanie Speidel, Shuo Li
PublisherSpringer Nature
Number of pages10
ISBN (Print)9783031164361
Publication statusPublished - 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13433 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


  • Acetabular index
  • Automated radiographic measurement
  • Clinical decision support system
  • Reimer’s migration percentage


Dive into the research topics of 'Automation of clinical measurements on radiographs of children's hips'. Together they form a unique fingerprint.

Cite this