Three-Dimensional Tissue Deformation Recovery and Tracking

Mountney, Peter; Stoyanov, Danail; Yang, Guang‐Zhong

doi:10.1109/msp.2010.936728

Cited by 171 publications

(120 citation statements)

References 76 publications

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“…Many approaches have been proposed in literature in order to achieve more reliable, robust, and real-time depth measurement to represent a deforming environment. Some approaches are based on feature detection and tracking [13], allowing the recovery of a sparse surface. In [26], a semi-dense reconstructed surface is obtained using feature detection and propagating the information into neighboring regions.…”

Section: State Of the Artmentioning

confidence: 99%

Dense soft tissue 3D reconstruction refined with super-pixel segmentation for robotic abdominal surgery

et al. 2015

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Purpose: Single Incision Laparoscopic Surgery (SILS) decreases post-operative infections, but introduces limitations in the surgeon's manoeuverability and in the surgical field of view. This work aims at enhancing intraoperative surgical visualization by exploiting the 3D information about the surgical site. An interactive guidance system is proposed wherein the pose of pre-operative tissue models is updated online. A critical process involves the intraoperative acquisition of tissue surfaces. It can be achieved using stereoscopic imaging and 3D reconstruction techniques. This work contributes to this process by proposing new methods for improved dense 3D reconstruction of soft tissues, which allows a more accurate deformation identification and facilitates the registration process.Methods: Two methods for soft tissue 3D reconstruction are proposed: Method 1 follows the traditional approach of the block matching algorithm. Method 2 performs a non-parametric Modified Census Transform to be more robust to illumination variation. The Simple Linear Iterative Clustering (SLIC) super pixel al- gorithm is exploited for disparity refinement by filling holes in the disparity images.Results: The methods were validated using two video datasets from the Hamlyn Centre, achieving an accuracy of 2.95 mm and 1.66 mm respectively. A comparison with ground truth data demonstrated the disparity refinement procedure: (i) increases the number of reconstructed points by up to 43%; (ii) does not a↵ect the accuracy of the 3D reconstructions significantly.Conclusion: Both methods give results that compare favourably with the state-of-the-art methods. The computational time constraints their applicability in realtime, but can be greatly improved by using a GPU implementation.

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Section: State Of the Artmentioning

confidence: 99%

Dense soft tissue 3D reconstruction refined with super-pixel segmentation for robotic abdominal surgery

et al. 2015

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“…1 Sample stereo video frame pairs along with their respective disparity maps are presented in Figs. 6 and 7.…”

Section: Objective Stereoscopic Video Quality Assessmentmentioning

confidence: 99%

“…1 As far as the dental video clips is concerned, their original and disparity corrected 3-D versions were presented, while one laparoscopic video with no defects, one with SWVs, and a third one in which both SWVs and BW were detected and chosen. Stereoscopic as well as nonstereoscopic versions of all the videos were used for the subjective evaluation.…”

Section: Subjective Stereoscopic Video Quality Evaluationmentioning

confidence: 99%

“…Such recordings allow the estimation of tissue surface geometry and tissue deformation recovery, and help in accurate decision-making in minimally invasive surgery (MIS). 1 Maximally stable extremal regions (MSER), detected using the lowest image intensity as the starting point along with image gradient features, are employed as an aid to salient landmark selection on stereo laparoscopic data. 2 Feature matching is subsequently performed and three-dimensional (3-D) point reconstruction as well as temporal tracking are accomplished based on epipolar constraints.…”

Section: Introductionmentioning

confidence: 99%

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Stereoscopic medical data video quality issues

et al. 2016

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Abstract. Stereoscopic medical videos are recorded, e.g., in stereo endoscopy or during video recording medical/dental operations. This paper examines quality issues in the recorded stereoscopic medical videos, as insufficient quality may induce visual fatigue to doctors. No attention has been paid to stereo quality and ensuing fatigue issues in the scientific literature so far. Two of the most commonly encountered quality issues in stereoscopic data, namely stereoscopic window violations and bent windows, were searched for in stereo endoscopic medical videos. Furthermore, an additional stereo quality issue encountered in dental operation videos, namely excessive disparity, was detected and fixed. The conducted experiments prove the existence of such quality issues in stereoscopic medical data and highlight the need for their detection and correction.

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“…Optical techniques for laparoscopic 3-D surface reconstruction can roughly be divided into two categories [47]. Passive methods, such as stereoscopy [48]), shape-from-shading [49], shape-from-motion (SfM) [50], and simultaneous localization and mapping (SLAM) [51] need only endoscopic RGB images as input. Active methods, such as structured light [52,53] and ToF require controlled light to be projected into the environment.…”

Section: -D Endoscopy For Minimally Invasive Proceduresmentioning

confidence: 99%

Real-Time Range Imaging in Health Care: A Survey

Bauer

Seitel

Hofmann³

et al. 2013

Lecture Notes in Computer Science

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Abstract. The recent availability of dynamic, dense, and low-cost range imaging has gained widespread interest in health care. It opens up new opportunities and has an increasing impact on both research and commercial activities. This chapter presents a state-of-the-art survey on the integration of modern range imaging sensors into medical applications. The scope is to identify promising applications and methods, and to provide an overview of recent developments in this rapidly evolving domain. The survey covers a broad range of topics, including guidance in computer-assisted interventions, operation room monitoring and workflow analysis, touch-less interaction and on-patient visualization, as well as prevention and support in elderly care and rehabilitation. We put emphasis on dynamic and interactive tasks where real-time and dense 3-D imaging forms the key aspect. While considering different range imaging modalities that fulfill these requirements, we particularly investigate the impact of Time-of-Flight imaging in this domain. Eventually, we discuss practical demands and limitations, and open research issues and challenges that are of fundamental importance for the progression of the field.

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Three-Dimensional Tissue Deformation Recovery and Tracking

Cited by 171 publications

References 76 publications

Dense soft tissue 3D reconstruction refined with super-pixel segmentation for robotic abdominal surgery

Dense soft tissue 3D reconstruction refined with super-pixel segmentation for robotic abdominal surgery

Stereoscopic medical data video quality issues

Real-Time Range Imaging in Health Care: A Survey

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