Cognitive Vision in Robotic Surgery

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• Patent
  Ye M, 2015,

  Method and Apparatus

  , WO/2015/033147
  • Cite
• Conference paper
  Ye M, Johns E, Giannarou S, Yang G-Zet al., 2014,

  Online Scene Association for Endoscopic Navigation

  , 17th International Conference MICCAI 2014, Publisher: Springer International Publishing, Pages: 316-323, ISSN: 0302-9743

  Endoscopic surveillance is a widely used method for moni-toring abnormal changes in the gastrointestinal tract such as Barrett'sesophagus. Direct visual assessment, however, is both time consumingand error prone, as it involves manual labelling of abnormalities on alarge set of images. To assist surveillance, this paper proposes an onlinescene association scheme to summarise an endoscopic video into scenes,on-the-y. This provides scene clustering based on visual contents, andalso facilitates topological localisation during navigation. The proposedmethod is based on tracking and detection of visual landmarks on thetissue surface. A generative model is proposed for online learning of pair-wise geometrical relationships between landmarks. This enables robustdetection of landmarks and scene association under tissue deformation.Detailed experimental comparison and validation have been conductedon in vivo endoscopic videos to demonstrate the practical value of ourapproach.

  • Abstract
  • Open Access Link
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• Conference paper
  Ye M, Johns E, Giannarou S, Yang GZet al., 2014,

  Online scene association for endoscopic navigation

  , Pages: 316-323

  Endoscopic surveillance is a widely used method for monitoring abnormal changes in the gastrointestinal tract such as Barrett's esophagus. Direct visual assessment, however, is both time consuming and error prone, as it involves manual labelling of abnormalities on a large set of images. To assist surveillance, this paper proposes an online scene association scheme to summarise an endoscopic video into scenes, on-the-fly. This provides scene clustering based on visual contents, and also facilitates topological localisation during navigation. The proposed method is based on tracking and detection of visual landmarks on the tissue surface. A generative model is proposed for online learning of pairwise geometrical relationships between landmarks. This enables robust detection of landmarks and scene association under tissue deformation. Detailed experimental comparison and validation have been conducted on in vivo endoscopic videos to demonstrate the practical value of our approach.

  • Abstract
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  • Citations: 4
• Conference paper
  Giannarou S, Gruijthuijsen C, Yang G-Z, 2014,

  Modeling and Recognition of Ongoing Surgical Gestures in TAVI Procedures

  • Cite
• Conference paper
  Shi C, Giannarou S, Lee S-L, Yang G-Zet al., 2014,

  Simultaneous Catheter and Environment Modeling for Trans-catheter Aortic Valve Implantation

  • Cite
• Conference paper
  Ye M, Giannarou S, Patel N, Teare J, Yang G-Zet al., 2013,

  Pathological Site Retargeting under Tissue Deformation Using Geometrical Association and Tracking

  , 16th International Conference on MICCAI 2013, Publisher: Springer Berlin Heidelberg, Pages: 67-74, ISSN: 0302-9743

  Recent advances in microscopic detection techniques includefluorescence spectroscopy, fibred confocal microscopy and optical coher-ence tomography. These methods can be integrated with miniaturisedprobes to assist endoscopy, thus enabling diseases to be detected at anearly and pre-invasive stage, forgoing the need for histopathological sam-ples and off-line analysis. Since optical-based biopsy does not leave vis-ible marks after sampling, it is important to track the biopsy sites toenable accurate retargeting and subsequent serial examination. In thispaper, a novel approach is proposed for pathological site retargeting ingastroscopic examinations. The proposed method is based on affine defor-mation modelling with geometrical association combined with cascadedonline learning and tracking. It provides online in vivo retargeting, and is able to track pathological sites in the presence of tissue deformation. It is also robust to partial occlusions and can be applied to a range of imaging probes including confocal laser endomicroscopy.

  • Abstract
  • Open Access Link
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• Conference paper
  Elmikaty M, Stathaki T, Kimber P, Giannarou Set al., 2013,

  A novel two-level shape descriptor for pedestrian detection

  , SSPD 2012

  The demand for pedestrian detection and tracking algorithms is rapidly increasing with applications in security systems, human computer interaction and human activity analysis. A pedestrian is a person standing in an upright position. Previous work involves using various types of image descriptors to detect humans. However, the existing approaches, although exhibit low misdetection rate, result in high rate of false alarms in the case of complex image backgrounds. In this work, a novel approach for pedestrian detection is proposed which is based on the combined use of two object detection approaches with the aim of reducing the false alarm rate of the individual detectors. These are the Histogram of Oriented Gradients (HOG) and a Shape Context based object detector (SC). Preliminary results are very encouraging and demonstrate clearly the ability of the proposed system to reduce the number of false alarms without significant increase in the processing time.

  • Abstract
  • Open Access Link
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• Conference paper
  , 2013,

  Pathological site retargeting under tissue deformation using geometrical association and tracking.

  , Pages: 67-74

  Recent advances in microscopic detection techniques include fluorescence spectroscopy, fibred confocal microscopy and optical coherence tomography. These methods can be integrated with miniaturised probes to assist endoscopy, thus enabling diseases to be detected at an early and pre-invasive stage, forgoing the need for histopathological samples and off-line analysis. Since optical-based biopsy does not leave visible marks after sampling, it is important to track the biopsy sites to enable accurate retargeting and subsequent serial examination. In this paper, a novel approach is proposed for pathological site retargeting in gastroscopic examinations. The proposed method is based on affine deformation modelling with geometrical association combined with cascaded online learning and tracking. It provides online in vivo retargeting, and is able to track pathological sites in the presence of tissue deformation. It is also robust to partial occlusions and can be applied to a range of imaging probes including confocal laser endomicroscopy.

  • Abstract
  • Cite
• Journal article
  Giannarou S, Visentini-Scarzanella M, Yang G-Z, 2013,

  Probabilistic Tracking of Affine-Invariant Anisotropic Regions

  , IEEE Trans. Pattern Anal. Machine Intell
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• Conference paper
  Vandini A, Giannarou S, Lee S-L, Yang G-Zet al., 2013,

  3D Robotic Catheter Shape Reconstruction and Localisation using Appearance Priors and Adaptive C-arm Positioning

  , Pages: 172-181
  • Cite

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