&lt;title&gt;Segmentation of colon lumen for virtual colonoscopy&lt;/title&gt;

Liang, Zach; Chen, Dongqing; Chiou, Rui C. H.; Li, Bin; Kaufman, Arie; Wax, Mark R.

doi:10.1117/12.349597

Cited by 19 publications

(17 citation statements)

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“…Fig. 3(a)-(c) displays the three mixture fields of air, soft tissue, and tagged fecal material, after performing five iterations of the Poisson-based derivative smoothing based on (10). Compared to Fig.…”

Section: Poisson-based Derivative Smoothingmentioning

confidence: 97%

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Electronic Cleansing in Fecal-Tagging Dual-Energy CT Colonography Based on Material Decomposition and Virtual Colon Tagging

Cai

Lee

Zhang

et al. 2015

IEEE Trans. Biomed. Eng.

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Dual-energy CT provides a promising solution to identify tagged fecal materials in electronic cleansing (EC) for fecal-tagging CT colonography (CTC). In this study, we developed a new EC method based on virtual colon tagging (VCT) for minimizing EC artifacts by use of the material decomposition ability in dual-energy CTC images. In our approach, a localized three-material decomposition model decomposes each voxel into a material mixture vector and the first partial derivatives of three base materials: luminal air, soft tissue, and iodine-tagged fecal material. A Poisson-based derivative smoothing algorithm smoothes the derivatives and implicitly smoothes the associated material mixture fields. VCT is a means for marking the entire colonic lumen by virtually elevating the CT value of luminal air as high as that of the tagged fecal materials to differentiate effectively soft-tissue structures from air-tagging mixtures. A dual-energy EC scheme based on VCT method, denoted as VCT-EC, was developed, in which the colonic lumen was first virtually tagged and then segmented by its high values in VCT images. The performance of the VCT-EC scheme was evaluated in a phantom study and a clinical study. Our results demonstrated that our VCT-EC scheme may provide a significant reduction of EC artifacts.

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Section: Poisson-based Derivative Smoothingmentioning

confidence: 97%

“…The early work on EC dates back to the late 1990s [8]- [10]. The term "EC" was first introduced by Wax et al [8].…”

Section: Introductionmentioning

confidence: 99%

Electronic Cleansing in Fecal-Tagging Dual-Energy CT Colonography Based on Material Decomposition and Virtual Colon Tagging

Cai

Lee

Zhang

et al. 2015

IEEE Trans. Biomed. Eng.

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“…The early work on EC dates back to the late 1990s (13)(14)(15). The term electronic cleansing was first introduced by Wax et al (13).…”

Section: Introductionmentioning

confidence: 99%

Informatics in Radiology: Dual-Energy Electronic Cleansing for Fecal-Tagging CT Colonography

Cai¹,

Kim²,

Lee³

et al. 2013

RadioGraphics

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Electronic cleansing (EC) is an emerging technique for the removal of tagged fecal materials at fecal-tagging computed tomographic (CT) colonography. However, existing EC methods may generate various types of artifacts that severely impair the quality of the cleansed CT colonographic images. Dual-energy fecal-tagging CT colonography is regarded as a nextgeneration imaging modality. EC that makes use of dual-energy fecal-tagging CT colonographic images promises to be effective in reducing cleansing artifacts by means of applying the material decomposition capability of dual-energy CT. The dual-energy index (DEI), which is calculated from the relative change in the attenuation values of a material at two different photon energies, is a reliable and effective indicator for differentiating tagged fecal materials from various types of tissues on fecal-tagging CT colonographic images. A DEI-based dual-energy EC scheme uses the DEI to help differentiate the colonic lumen-including the luminal air, tagged fecal materials, and air-tagging mixture-from the colonic soft-tissue structures, and then segments the entire colonic lumen for cleansing of the tagged fecal materials. As a result, dual-energy EC can help identify partialvolume effects in the air-tagging mixture and inhomogeneous tagging in residual fecal materials, the major causes of EC artifacts. This technique has the potential to significantly improve the quality of EC and promises to provide images of a cleansed colon that are free of the artifacts commonly observed with conventional single-energy EC methods.

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“…In this paper, we focus on developing a statistical method of maximum a posterior probability (MAP) for an optimal classification. We extended our previous reported MAP-EM (Expectation Maximization) segmentation approach [9,10,11,12] by utilizing a hidden Markov random field (MRF) Gibbs model [19]. In this model, the spatial information of a selected voxel was integrated into the well-established MAP-EM modelfitting algorithm, thus overcoming the non-uniformity problems in the tagged stool/fluid region.…”

Section: Introductionmentioning

confidence: 99%

“…However, this physical bowel washing is often unpleasant to patients. We have developed an alternative approach, termed electronic colon cleansing to virtually clean the colon lumen, therefore, eliminating or minimizing physical bowel washing [2,11,12,17]. Based on our preliminary studies, residual stool and fluid are often problematic for virtual colonoscopy.…”

Section: Introductionmentioning

confidence: 99%

Image segmentation approach to extract colon lumen through colonic material tagging and hidden Markov random field model for virtual colonoscopy

Chen

Lakare

et al. 2002

SPIE Proceedings

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Virtual colonoscopy provides a safe, minimal-invasive approach to detect colonic polyps using medical imaging and computer graphics technologies. Residual stool and fluid are problematic for optimal viewing of the colonic mucosa. Electronic cleansing techniques combining bowel preparation, oral contrast agents, and image segmentation were developed to extract the colon lumen from computed tomography (CT) images of the colon. In this paper, we present a new electronic colon cleansing technology, which employs a hidden Markov random filed (MRF) model to integrate the neighborhood information for overcoming the non-uniformity problems within the tagged stool/fluid region. Prior to obtaining CT images, the patient undergoes a bowel preparation. A statistical method for maximum a posterior probability (MAP) was developed to identify the enhanced regions of residual stool/fluid. The method utilizes a hidden MRF Gibbs model to integrate the spatial information into the Expectation Maximization (EM) model-fitting MAP algorithm. The algorithm estimates the model parameters and segments the voxels iteratively in an interleaved manner, converging to a solution where the model parameters and voxel labels are stabilized within a specified criterion. Experimental results are promising.

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<title>Segmentation of colon lumen for virtual colonoscopy</title>

Cited by 19 publications

References 0 publications

Electronic Cleansing in Fecal-Tagging Dual-Energy CT Colonography Based on Material Decomposition and Virtual Colon Tagging

Electronic Cleansing in Fecal-Tagging Dual-Energy CT Colonography Based on Material Decomposition and Virtual Colon Tagging

Informatics in Radiology: Dual-Energy Electronic Cleansing for Fecal-Tagging CT Colonography

Image segmentation approach to extract colon lumen through colonic material tagging and hidden Markov random field model for virtual colonoscopy

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