Automatic detection and localization of bone erosion in hand HR-pQCT

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Jintao Ren, H. Arash Moaddel, Ellen M. Hauge, Kresten K. Keller, Rasmus K. Jensen, François Lauze

Rheumatoid arthritis (RA) is an inflammatory disease which afflicts the joints with arthritis and periarticular bone destruction as a result. One of its central features is bone erosion, a consequence of excessive bone resorption and insufficient bone formation. High-resolution peripheral quantitative computed tomography (HR-pQCT) is a promising tool for monitoring RA. Quantification of bone erosions and detection of possible progression is essential in the management of treatment. Detection is performed manually and is a very demanding task as rheumatologists must annotate hundreds of 2D images and inspect any region of the bone structure that is suspected to be a sign of RA. We propose a 2D based method which combines an accurate segmentation of bone surface boundary and classification of patches along the surface as healthy or eroded. We use a series of classical image processing methods to segment CT volumes semi-automatically. They are used as training data for a U-Net. We train a Siamese net to learn the difference between healthy and eroded patches. The Siamese net alleviates the problem of highly imbalanced class labels by providing a base for one-shot learning of differences between patches. We trained and tested the method using 3 full HR-pQCT scans with bone erosion of various size. The proposed pipeline succeeded in classifying healthy and eroded patches with high precision and recall. The proposed algorithm is a preliminary work to demonstrate the potential of our pipeline in automating the process of detecting and locating the eroded regions of bone surfaces affected by RA.

Original languageEnglish
Title of host publicationMedical Imaging 2019 : Computer-Aided Diagnosis
EditorsKensaku Mori, Horst K. Hahn
Number of pages9
PublisherSPIE - International Society for Optical Engineering
Publication date2019
Article number1095022
ISBN (Electronic)9781510625471
DOIs
Publication statusPublished - 2019
EventMedical Imaging 2019: Computer-Aided Diagnosis - San Diego, United States
Duration: 17 Feb 201920 Feb 2019

Conference

ConferenceMedical Imaging 2019: Computer-Aided Diagnosis
LandUnited States
BySan Diego
Periode17/02/201920/02/2019
SponsorThe Society of Photo-Optical Instrumentation Engineers (SPIE)
SeriesProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume10950
ISSN1605-7422

    Research areas

  • Active Contours, Bone Erosion, HR-pQCT, Rheumatoid Arthritis, Siamese Nets, U-Nets

ID: 227331677