Episode Classification for the Analysis of Tissue/Instrument Interaction with Multiple Visual Cues

Lo, Benny; Darzi, Ara; Yang, Guang‐Zhong

doi:10.1007/978-3-540-39899-8_29

Cited by 34 publications

(25 citation statements)

References 10 publications

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“…There are several ways to deal with this problem. One way is to design classifiers that detect certain instruments or aspects of a surgery as for example done by [4,5]. When developing such a classifier, the feature space is usually reduced by manually choosing features that work well for a certain instrument.…”

Section: Signalsmentioning

confidence: 99%

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Modeling and Segmentation of Surgical Workflow from Laparoscopic Video

Blum

Feußner

Navab

2010

Lecture Notes in Computer Science

126

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Abstract. Modeling and analyzing surgeries based on signals that are obtained automatically from the operating room (OR) is a field of recent interest. It can be valuable for analyzing and understanding surgical workflow, for skills evaluation and developing context-aware ORs. In minimally invasive surgery, laparoscopic video is easy to record but it is challenging to extract meaningful information from it. We propose a method that uses additional information about tool usage to perform a dimensionality reduction on image features. Using Canonical Correlation Analysis (CCA) a projection of a high-dimensional image feature space to a low dimensional space is obtained such that semantic information is extracted from the video. To model a surgery based on the signals in the reduced feature space two different statistical models are compared. The capability of segmenting a new surgery into phases only based on the video is evaluated. Dynamic Time Warping which strongly depends on the temporal order in combination with CCA shows the best results.

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Section: Signalsmentioning

confidence: 99%

“…In laparoscopic surgery, video images are one important source of information. In [4] instrument segmentation and tracking, tissue deformation and changes in specular highlights are detected from laparoscopic video. This data has been used to classify four different states.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Segmentation of Surgical Workflow from Laparoscopic Video

Blum

Feußner

Navab

2010

Lecture Notes in Computer Science

126

View full text Add to dashboard Cite

show abstract

“…For a detailed analysis of visual search and hand/eye strategy, the surgical task was decomposed into two steps: vessel grasping (task 1) and vessel transection (task 2). Each AOI was defined by different colours and automatically tracked by colour segmentation by hue-saturation space filtering previously described [12]. The co-ordinates of each AOI were combined with the gaze data and using developed software we determined which AOI foveal vision (taken as 2° visual angle) was centered.…”

Section: Analysis Of Fixation and Visual Search Strategymentioning

confidence: 99%

A Study of Saccade Transition for Attention Segregation and Task Strategy in Laparoscopic Surgery

Nicolaou

James

Darzi

et al. 2004

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004

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Abstract. The advent and accelerated adoption of laparoscopic surgery requires an objective assessment of both operative performance and perceptual events that lead to clinical decisions. In this paper we present a framework to extract the underlying strategy through the analysis of saccadic eye-movements that lead to visual attention, and identification of intrinsic features central to the execution of basic laparoscopic tasks. Markov modeling is applied to the quantification of the saccadic eye movements for elucidating the intrinsic behaviour of the participants and the spatial-temporal evolution of visual search and hand/eye coordination characteristics. It has been found that participants adopted a unified strategy but the underlying disparity in saccadic behaviour reflect temporal and behavioural differences that could be indicative of the mental process by which the task was executed.

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“…Their analysis was based on augmented reality and computer vision techniques. Lo et al [2] used vision to segment the surgical episode. They used color segmentation, shape-from-shading techniques, and optical flows for tracking instruments.…”

Section: Introductionmentioning

confidence: 99%

An Application-Dependent Framework for the Recognition of High-Level Surgical Tasks in the OR

Lalys

Riffaud

Bouget

et al. 2011

Lecture Notes in Computer Science

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Abstract. Surgical process analysis and modeling is a recent and important topic aiming at introducing a new generation of computer-assisted surgical systems. Among all of the techniques already in use for extracting data from the Operating Room, the use of image videos allows automating the surgeons' assistance without altering the surgical routine. We proposed in this paper an application-dependent framework able to automatically extract the phases of the surgery only by using microscope videos as input data and that can be adaptable to different surgical specialties. First, four distinct types of classifiers based on image processing were implemented to extract visual cues from video frames. Each of these classifiers was related to one kind of visual cue: visual cues recognizable through color were detected with a color histogram approach, for shape-oriented visual cues we trained a Haar classifier, for texture-oriented visual cues we used a bag-of-word approach with SIFT descriptors, and for all other visual cues we used a classical image classification approach including a feature extraction, selection, and a supervised classification. The extraction of this semantic vector for each video frame then permitted to classify time series using either Hidden Markov Model or Dynamic Time Warping algorithms. The framework was validated on cataract surgeries, obtaining accuracies of 95%.

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Episode Classification for the Analysis of Tissue/Instrument Interaction with Multiple Visual Cues

Cited by 34 publications

References 10 publications

Modeling and Segmentation of Surgical Workflow from Laparoscopic Video

Modeling and Segmentation of Surgical Workflow from Laparoscopic Video

A Study of Saccade Transition for Attention Segregation and Task Strategy in Laparoscopic Surgery

An Application-Dependent Framework for the Recognition of High-Level Surgical Tasks in the OR

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