PublicationDetail

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

THIS WEBPAGE IS DEPRECATED - please visit our new website

M. Alsheakhali, A. Eslami, A. Roodaki, N. Navab
CRF-Based Model for Instrument Detection and Pose Estimation in Retinal Microsurgery
Computational and Mathematical Methods in Medicine, Special issue on Machine Learning Applications in Medical Image Analysis, 2016 (bib)

Detection of instrument tip in retinal microsurgery videos is extremely challenging due to rapid motion, illumination changes, the cluttered background and the deformable shape of the instrument. For the same reason, frequent failures in tracking add the overhead of re-initialization of the tracking. In this work, a new method is proposed to localize not only the instrument center point but also its tips and orientation without the need of manual re-initialization. Our approach models the instrument as a Conditional Random Fields (CRF) where each part of the instrument is detected separately. The relations between these parts are modeled to capture the translation, rotation and the scale changes of the instrument. The tracking is done via separate detection of instrument parts and evaluation of confidence via the modeled dependence functions. In case of low confidence feedback an automatic recovery process is performed. The algorithm is evaluated on in-vivo ophthalmic surgery datasets and its performance is comparable to the state-of-the-art methods with the advantage that no manual re-initialization is needed.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each authors copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.



Edit | Attach | Refresh | Diffs | More | Revision r1.13 - 30 Jan 2019 - 15:16 - LeslieCasas

Lehrstuhl für Computer Aided Medical Procedures & Augmented Reality    rss.gif