Re-localisation of a biopsy site in endoscopic images and characterisation of its uncertainty

Allain, Baptiste; Hu, Mingxing; Lovat, Laurence; Cook, Richard; Vercauteren, Tom; Ourselin, Sébastien; Hawkes, David J.

doi:10.1016/j.media.2011.11.005

Cited by 15 publications

(14 citation statements)

References 29 publications

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“…In their work, affine-covariant regions combined with geometric constraints are used to facilitate retargeting of optical biopsy sites. Epipolar geometry has been used in Allain et al (2012) such that for a query image, the biopsy is found by intersecting epipolar lines projected from a set of images where the biopsy site location is known. It should be noted that both of the above methods require multiple images that contain the same biopsy site.…”

Section: Related Work and Contributionsmentioning

confidence: 99%

Online tracking and retargeting with applications to optical biopsy in gastrointestinal endoscopic examinations

Giannarou

Meining

et al. 2016

Medical Image Analysis

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Section: Related Work and Contributionsmentioning

confidence: 99%

Online tracking and retargeting with applications to optical biopsy in gastrointestinal endoscopic examinations

Giannarou

Meining

et al. 2016

Medical Image Analysis

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“…In this paper, we assume regional tissue deformation can be modelled by local affine transformations, as similarly adopted in [3]. With this assumption, the appearance of a local surface patch in two different views can be linked with an affine transformation.…”

Section: Local Affine Tissue Deformation Modellingmentioning

confidence: 99%

“…These include the use of Markov Random Fields (MRF) [1], Simultaneous Localisation and Mapping (SLAM) [2], and a multi-view based approach using epipolar geometry [3]. To permit simultaneous retargeting and localisation during an entire examination procedure, endoscopic image classification in the manifold space has been used for surveillance endoscopy [4].…”

Section: Introductionmentioning

confidence: 99%

Pathological Site Retargeting under Tissue Deformation Using Geometrical Association and Tracking

Giannarou

Patel

et al. 2013

Advanced Information Systems Engineering

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Abstract. 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.

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“…For intra-examination, retargeting techniques using local image features have been proposed, which include feature matching [1], geometric transformations [2], tracking [3,4], and mapping [5]. However, when applied over successive examinations, these often fail due to the long-term variation in appearance of tissue surface, which causes difficulty in detecting the same local features.…”

Section: Introductionmentioning

confidence: 99%

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

Johns

Walter

et al. 2016

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016

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For early diagnosis of malignancies in the gastrointestina l tract, surveillance endoscopy is increasingly used to moni tor abnormal tissue changes in serial examinations of the same patient. D espite suc- cesses with optical biopsy for in vivo and in situ tissue characterisa- tion, biopsy retargeting for serial examinations is challe nging because tissue may change in appearance between examinations. In th is paper, we propose an inter-examination retargeting framework for op tical biopsy, based on an image descriptor designed for matching between e ndoscopic scenes over significant time intervals. Each scene is descri bed by a hierar- chy of regional intensity comparisons at various scales, off ering tolerance to long-term change in tissue appearance whilst remaining d iscrimina- tive. Binary coding is then used to compress the descriptor v ia a novel random forests approach, providing fast comparisons in Ham ming space and real-time retargeting. Extensive validation conducte d on 13 in vivo gastrointestinal videos, collected from six patients, sho w that our ap- proach outperforms state-of-the-art methods

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Re-localisation of a biopsy site in endoscopic images and characterisation of its uncertainty

Cited by 15 publications

References 29 publications

Online tracking and retargeting with applications to optical biopsy in gastrointestinal endoscopic examinations

Online tracking and retargeting with applications to optical biopsy in gastrointestinal endoscopic examinations

Pathological Site Retargeting under Tissue Deformation Using Geometrical Association and Tracking

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

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