Paper
24 February 2012 A new automatic landmark extraction framework on ultrasound images of femoral condyles
Agnès Masson-Sibut, Amir Nakib, Eric Petit, François Leitner
Author Affiliations +
Abstract
In Computer Assisted Orthopaedic Surgery (CAOS), surgeons have to acquire some anatomical landmarks as inputs to the system. To do so, they use manual pointers that are localized in the Operating Room (OR) space using an infrared camera. When the needed landmark is not reachable through an opening, it is palpated directly on skin and there is a loss of precision that can vary from several millimeters to centimeters depending on the thickness of soft tissues. In this paper, we propose a new framework based on three main steps to register the bone surface and extract automatically anatomical landmarks with an ultrasound probe. This framework is based on an oriented gradient calculation, a simulated-compound and a contour closure using a graph representation. The oriented gradient allows extracting a set of pixels that probably belong to the bone surface. The simulatedcompound step allows using ultrasound images properties to define a set of small segments which may belong to the bone surface, and the graph representation allows eliminating false positive detection among remaining segments. The proposed method has been validated on a database of 230 ultrasound images of anterior femoral condyles (on the knee). The average computation time is 0.11 sec per image, and average errors are: 0.54 mm for the bone surface extraction, 0.31 mm for the condylar line, and 1.4 mm for the trochlea middle.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Agnès Masson-Sibut, Amir Nakib, Eric Petit, and François Leitner "A new automatic landmark extraction framework on ultrasound images of femoral condyles", Proc. SPIE 8320, Medical Imaging 2012: Ultrasonic Imaging, Tomography, and Therapy, 83200U (24 February 2012); https://doi.org/10.1117/12.910604
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Cited by 1 scholarly publication.
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KEYWORDS
Image segmentation

Bone

Ultrasonography

Surgery

Ultrasonics

Databases

Silicon

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