Abstract
Ultrasound (US) could become a standard of care imaging modality for the quantitative assessment of femoral cartilage thickness for the early diagnosis of knee osteoarthritis. However, low contrast, high levels of speckle noise, and various imaging artefacts hinder the analysis of collected data. Accurate, robust, and fully automatic US image-enhancement and cartilage-segmentation methods are needed in order to improve the widespread deployment of this imaging modality for knee-osteoarthritis diagnosis and monitoring. In this work, we propose a method based on local-phase-based image processing for automatic knee-cartilage image enhancement, segmentation, and thickness measurement. A local-phase feature-guided dynamic-programming approach is used for the fully automatic localization of knee-bone surfaces. The localized bone surfaces are used as seed points for automating the seed-guided segmentation of the cartilage. We evaluated the Random Walker (RW), watershed, and graph-cut-based segmentation methods from 200 scans obtained from ten healthy volunteers. Validation against manual expert segmentation achieved a mean dice similarity coefficient of 0.90, 0.86, and 0.84 for the RW, watershed, and graph-cut segmentation methods, respectively. Automatically segmented cartilage regions achieved 0.18 mm localization accuracy compared to manual expert thickness measurement.
Highlights
Osteoarthritis (OA) of the knee joint is the most common type of arthritis in elderly people [1].It occurs when the cartilage between the knee joints starts to degenerate and wears away
Investigating the results, we can infer that the Random Walker (RW) algorithm yielded better cartilage segmentation, whereas the watershed and graph-cut algorithms are limited by over- and undersegmentation for various cartilage sections
Qualitative results show that the RW algorithm yielded better cartilage segmentation, whereas watershed and graph-cut were limited by oversegmentation
Summary
Osteoarthritis (OA) of the knee joint is the most common type of arthritis in elderly people [1]. It occurs when the cartilage between the knee joints starts to degenerate and wears away. The bones of the joints glide closely against each other causing pain, lack of mobility between the joints, and swelling. Detection and improved monitoring is important for the treatment of OA. Imaging plays an important role during OA detection and management. X-ray planar radiography is the standard imaging modality used in clinical practice for diagnosing OA and monitoring disease progression [2]. Osteophytes, subchondral cysts, and sclerosis, associated with
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
