The Centre has a long history of developing new techniques for medical imaging (particularly in magnetic resonance imaging), transforming them from a primarily diagnostic modality into an interventional and therapeutic platform. This is facilitated by the Centre's strong engineering background in practical imaging and image analysis platform development, as well as advances in minimal access and robotic assisted surgery. Hamlyn has a strong tradition in pursuing basic sciences and theoretical research, with a clear focus on clinical translation.

In response to the current paradigm shift and clinical demand in bringing cellular and molecular imaging modalities to an in vivo – in situ setting during surgical intervention, our recent research has also been focussed on novel biophotonics platforms that can be used for real-time tissue characterisation, functional assessment, and intraoperative guidance during minimally invasive surgery. This includes, for example, SMART confocal laser endomicroscopy, time-resolved fluorescence spectroscopy and flexible FLIM catheters.

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    Ye M, Johns E, Walter B, Meining A, Yang G-Zet al., 2016,

    Robust Image Descriptors for Real-Time Inter-Examination Retargeting in Gastrointestinal Endoscopy

    , International Conference on Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016, Publisher: Springer, Pages: 448-456, ISSN: 0302-9743

    For early diagnosis of malignancies in the gastrointestinaltract, surveillance endoscopy is increasingly used to monitor abnormaltissue changes in serial examinations of the same patient. Despite suc-cesses with optical biopsy forin vivoandin situtissue characterisa-tion, biopsy retargeting for serial examinations is challenging becausetissue may change in appearance between examinations. In this paper, wepropose an inter-examination retargeting framework for optical biopsy,based on an image descriptor designed for matching between endoscopicscenes over significant time intervals. Each scene is described by a hierar-chy of regional intensity comparisons at various scales, offering toleranceto long-term change in tissue appearance whilst remaining discrimina-tive. Binary coding is then used to compress the descriptor via a novelrandom forests approach, providing fast comparisons in Hamming spaceand real-time retargeting. Extensive validation conducted on 13in vivogastrointestinal videos, collected from six patients, show that our ap-proach outperforms state-of-the-art methods.

    Ye M, Zhang L, Giannarou S, Yang G-Zet al., 2016,

    Real-Time 3D Tracking of Articulated Tools for Robotic Surgery

    , International Conference on Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016, Publisher: Springer, Pages: 386-394, ISSN: 0302-9743

    In robotic surgery, tool tracking is important for providingsafe tool-tissue interaction and facilitating surgical skills assessment. De-spite recent advances in tool tracking, existing approaches are faced withmajor difficulties in real-time tracking of articulated tools. Most algo-rithms are tailored for offline processing with pre-recordedvideos. In thispaper, we propose a real-time 3D tracking method for articulated toolsin robotic surgery. The proposed method is based on the CAD modelof the tools as well as robot kinematics to generate online part-basedtemplates for efficient 2D matching and 3D pose estimation. A robustverification approach is incorporated to reject outliers in2D detections,which is then followed by fusing inliers with robot kinematic readingsfor 3D pose estimation of the tool. The proposed method has been val-idated with phantom data, as well asex vivoandin vivoexperiments.The results derived clearly demonstrate the performance advantage ofthe proposed method when compared to the state-of-the-art.

    Zhao L, Giannarou S, Lee S, Yang GZet al.,

    Registration-free simultaneous catheter and environment modelling

    , Medical Image Computing and Computer Assisted Intervention (MICCAI) 2016, Publisher: Springer

    Endovascular procedures are challenging to perform due tothe complexity and difficulty in catheter manipulation. The simultaneousrecovery of the 3D structure of the vasculature and the catheter posi-tion and orientation intra-operatively is necessary in catheter controland navigation. State-of-art Simultaneous Catheter and EnvironmentModelling provides robust and real-time 3D vessel reconstruction based on real-time intravascular ultrasound (IVUS) imaging and electromagnetic (EM) sensing, but still relies on accurate registration between EM and pre-operative data. In this paper, a registration-free vessel reconstruction method is proposed for endovascular navigation. In the optimisation framework, the EM-CT registration is estimated and updated intra-operatively together with the 3D vessel reconstruction from IVUS, EM and pre-operative data, and thus does not require explicit registration. The proposed algorithm can also deal with global (patient) motion and periodic deformation caused by cardiac motion. Phantom and in-vivo experiments validate the accuracy of the algorithm and the resultsdemonstrate the potential clinical value of the technique.

    Zhou X, Riga C, Yang G, Lee Set al., 2016,

    3D Shape Recovery of Deployed Stent Grafts from a Single X-ray Image based on Newly Designed Markers

    , MICCAI Workshop on CVII-STENT 2016
    Smith R, Lee S, Bicknell C, Riga Cet al.,

    Examining the use of a novel dynamic endovascular simulator to facilitate intelligent localization and robotic technologies

    , The Vascular Societies’ ASM 2016

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