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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  • Journal article
    Kassahun Y, Yu B, Tibebu AT, Stoyanov D, Giannarou S, Metzen JH, Vander Poorten Eet al., 2015,

    Surgical robotics beyond enhanced dexterity instrumentation: a survey of machine learning techniques and their role in intelligent and autonomous surgical actions

    , International Journal of Computer Assisted Radiology and Surgery, Vol: 11, Pages: 553-568, ISSN: 1861-6410

    PurposeAdvances in technology and computing play an increasingly important role in the evolution of modern surgical techniques and paradigms. This article reviews the current role of machine learning (ML) techniques in the context of surgery with a focus on surgical robotics (SR). Also, we provide a perspective on the future possibilities for enhancing the effectiveness of procedures by integrating ML in the operating room.MethodsThe review is focused on ML techniques directly applied to surgery, surgical robotics, surgical training and assessment. The widespread use of ML methods in diagnosis and medical image computing is beyond the scope of the review. Searches were performed on PubMed and IEEE Explore using combinations of keywords: ML, surgery, robotics, surgical and medical robotics, skill learning, skill analysis and learning to perceive.ResultsStudies making use of ML methods in the context of surgery are increasingly being reported. In particular, there is an increasing interest in using ML for developing tools to understand and model surgical skill and competence or to extract surgical workflow. Many researchers begin to integrate this understanding into the control of recent surgical robots and devices.ConclusionML is an expanding field. It is popular as it allows efficient processing of vast amounts of data for interpreting and real-time decision making. Already widely used in imaging and diagnosis, it is believed that ML will also play an important role in surgery and interventional treatments. In particular, ML could become a game changer into the conception of cognitive surgical robots. Such robots endowed with cognitive skills would assist the surgical team also on a cognitive level, such as possibly lowering the mental load of the team. For example, ML could help extracting surgical skill, learned through demonstration by human experts, and could transfer this to robotic skills. Such intelligent surgical assistance would significantly surpass the st

  • Journal article
    Keir GJ, Nair A, Giannarou S, Yang G-Z, Oldershaw P, Wort SJ, MacDonald P, Hansell DM, Wells AUet al., 2015,

    Pulmonary vasospasm in systemic sclerosis: noninvasive techniques for detection

    , Pulmonary Circulation, Vol: 5, Pages: 498-505, ISSN: 2045-8940

    In a subgroup of patients with systemic sclerosis (SSc), vasospasm affecting the pulmonary circulation may contribute to worsening respiratory symptoms, including dyspnea. Noninvasive assessment of pulmonary blood flow (PBF), utilizing inert-gas rebreathing (IGR) and dual-energy computed-tomography pulmonary angiography (DE-CTPA), may be useful for identifying pulmonary vasospasm. Thirty-one participants (22 SSc patients and 9 healthy volunteers) underwent PBF assessment with IGR and DE-CTPA at baseline and after provocation with a cold-air inhalation challenge (CACh). Before the study investigations, participants were assigned to subgroups: group A included SSc patients who reported increased breathlessness after exposure to cold air (n = 11), group B included SSc patients without cold-air sensitivity (n = 11), and group C patients included the healthy volunteers. Median change in PBF from baseline was compared between groups A, B, and C after CACh. Compared with groups B and C, in group A there was a significant decline in median PBF from baseline at 10 minutes (−10%; range: −52.2% to 4.0%; P < 0.01), 20 minutes (−17.4%; −27.9% to 0.0%; P < 0.01), and 30 minutes (−8.5%; −34.4% to 2.0%; P < 0.01) after CACh. There was no significant difference in median PBF change between groups B or C at any time point and no change in pulmonary perfusion on DE-CTPA. Reduction in pulmonary blood flow following CACh suggests that pulmonary vasospasm may be present in a subgroup of patients with SSc and may contribute to worsening dyspnea on exposure to cold.

  • Journal article
    Shen M, Giannarou S, Yang G-Z, 2015,

    Robust camera localisation with depth reconstruction for bronchoscopic navigation

    , International Journal of Computer Assisted Radiology and Surgery, Vol: 10, Pages: 801-813, ISSN: 1861-6410

    PurposeBronchoscopy is a standard technique for airway examination, providing a minimally invasive approach for both diagnosis and treatment of pulmonary diseases. To target lesions identified pre-operatively, it is necessary to register the location of the bronchoscope to the CT bronchial model during the examination. Existing vision-based techniques rely on the registration between virtually rendered endobronchial images and videos based on image intensity or surface geometry. However, intensity-based approaches are sensitive to illumination artefacts, while gradient-based approaches are vulnerable to surface texture.MethodsIn this paper, depth information is employed in a novel way to achieve continuous and robust camera localisation. Surface shading has been used to recover depth from endobronchial images. The pose of the bronchoscopic camera is estimated by maximising the similarity between the depth recovered from a video image and that captured from a virtual camera projection of the CT model. The normalised cross-correlation and mutual information have both been used and compared for the similarity measure.ResultsThe proposed depth-based tracking approach has been validated on both phantom and in vivo data. It outperforms the existing vision-based registration methods resulting in smaller pose estimation error of the bronchoscopic camera. It is shown that the proposed approach is more robust to illumination artefacts and surface texture and less sensitive to camera pose initialisation.ConclusionsA reliable camera localisation technique has been proposed based on depth information for bronchoscopic navigation. Qualitative and quantitative performance evaluations show the clinical value of the proposed framework.

  • Conference paper
    Karlas A, Su-Lin Lee, 2015,

    Towards an IVUS-driven system for endovascular navigation

    , Biomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on, Pages: 1324-1327
  • Patent
    Ye M, 2015,

    Method and Apparatus

    , WO/2015/033147

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