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
    Shen M, Tenda ED, McNulty W, Garner J, Robbie H, Luzzi V, Aboelhassan AM, Van Geffen WH, Kemp SV, Ridge C, Devaraj A, Shah PL, Yang G-Zet al., 2019,

    Quantitative Evaluation of Lobar Pulmonary Function of Emphysema Patients with Endobronchial Coils

    , RESPIRATION, Vol: 98, Pages: 70-81, ISSN: 0025-7931
  • Journal article
    Giataganas P, Hughes M, Payne C, Wisanuvej P, Temelkuran B, Yang GZet al., 2019,

    Intraoperative robotic-assisted large-area high-speed microscopic imaging and intervention

    , IEEE Transactions on Biomedical Engineering, Vol: 66, Pages: 208-216, ISSN: 0018-9294

    IEEE Objective: Probe-based confocal endomicroscopy is an emerging high-magnification optical imaging technique that provides in-vivo and in-situ cellular-level imaging for real-time assessment of tissue pathology. Endomicroscopy could potentially be used for intraoperative surgical guidance, but it is challenging to assess a surgical site using individual microscopic images due to the limited field-of-view and difficulties associated with manually manipulating the probe. Methods: In this paper, a novel robotic device for large-area endomicroscopy imaging is proposed, demonstrating a rapid, but highly accurate, scanning mechanism with image-based motion control which is able to generate histology-like endomicroscopy mosaics. The device also includes, for the first time in robotic-assisted endomicroscopy, the capability to ablate tissue without the need for an additional tool. Results: The device achieves pre-programmed trajectories with positioning accuracy of less than 30um, the image-based approach demonstrated that it can suppress random motion disturbances up to 1.25mm/s. Mosaics are presented from a range of ex-vivo human and animal tissues, over areas of more than 3mm<formula><tex>$^2$</tex></formula>, scanned in approximate 10s. Conclusion: This work demonstrates the potential of the proposed instrument to generate large-area, high-resolution microscopic images for intraoperative tissue identification and margin assessment. Significance: This approach presents an important alternative to current histology techniques, significantly reducing the tissue assessment time, while simultaneously providing the capability to mark and ablate suspicious areas intraoperatively.

  • Journal article
    Tudor A, Delaney C, Zhang H, Thompson AJ, Curto VF, Yang GZ, Higgins MJ, Diamond D, Florea Let al., 2018,

    Fabrication of soft, stimulus-responsive structures with sub-micron resolution via two-photon polymerization of poly(ionic liquid)s

    , Materials Today, Vol: 21, Pages: 807-816, ISSN: 1369-7021

    Soft, stimulus-responsive 3D structures created from crosslinked poly(ionic liquid)s (PILs) have been fabricated at unprecedented sub-micron resolution by direct laser writing (DLW). These structures absorb considerable quantities of solvent (e.g., water, alcohol, and acetone) to produce PIL hydrogels that exhibit stimulus-responsive behavior. Due to their flexibility and soft, responsive nature, these structures are much more akin to biological systems than the conventional, highly crosslinked, rigid structures typically produced using 2-photon polymerization (2-PP). These PIL gels expand/contract due to solvent uptake/release, and, by exploiting inherited properties of the ionic liquid monomer (ILM), thermo-responsive gels that exhibit reversible area change (30 ± 3%, n = 40) when the temperature is raised from 20 °C to 70 °C can be created. The effect is very rapid, with the response indistinguishable from the microcontroller heating rate of 7.4 °C s−1. The presence of an endoskeleton-like framework within these structures influences movement arising from expansion/contraction and assists the retention of structural integrity during actuation cycling.

  • Conference paper
    Gu Y, Vyas K, Yang J, Yang GZet al., 2018,

    Weakly supervised representation learning for endomicroscopy image analysis

    , Medical Image Computing and Computer Assisted Intervention – MICCAI 2018, Publisher: Springer, Pages: 326-334, ISSN: 0302-9743

    This paper proposes a weakly-supervised representation learning framework for probe-based confocal laser endomicroscopy (pCLE). Unlike previous frame-based and mosaic-based methods, the proposed framework adopts deep convolutional neural networks and integrates frame-based feature learning, global diagnosis prediction and local tumor detection into a unified end-to-end model. The latent objects in pCLE mosaics are inferred via semantic label propagation and the deep convolutional neural networks are trained with a composite loss function. Experiments on 700 pCLE samples demonstrate that the proposed method trained with only global supervisions is able to achieve higher accuracy on global and local diagnosis prediction.

  • Conference paper
    Triantafyllou P, Wisanuvej P, Giannarou S, Liu J, Yang G-Zet al., 2018,

    A Framework for Sensorless Tissue Motion Tracking in Robotic Endomicroscopy Scanning

    , IEEE International Conference on Robotics and Automation (ICRA), Publisher: IEEE COMPUTER SOC, Pages: 2694-2699, ISSN: 1050-4729

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