Teniae Coli Guided Navigation and Registration for Virtual Colonoscopy

Huang, Adam; Roy, Dave A.; Franaszek, Marek; Summers, Ronald M.

doi:10.1109/vis.2005.96

Cited by 22 publications

(18 citation statements)

References 21 publications

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“…Our method has advantages compared to several previous works on teniae coli detection. The work of Huang et al 13,14 is the earliest investigation on this problem. They manually localized TO and subsequently derived TM and TL by assuming the distance between every two teniae is equal.…”

Section: Discussionmentioning

confidence: 99%

Automated teniae coli detection and identification on computed tomographic colonography

et al. 2012

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Purpose: Computed tomographic colonography (CTC) is a minimally invasive technique for colonic polyps and cancer screening. Teniae coli are three bands of longitudinal smooth muscle on the colon surface. Teniae coli are important anatomically meaningful landmarks on human colon. In this paper, the authors propose an automatic teniae coli detection method for CT colonography. Methods: The original CTC slices are first segmented and reconstructed to a 3D colon surface. Then, the 3D colon surface is unfolded using a reversible projection technique. After that the unfolded colon is projected to a 2D height map. The teniae coli are detected using the height map and then reversely projected back to the 3D colon. Since teniae are located at the junctions where the haustral folds meet, the authors apply 2D Gabor filter banks to extract features of haustral folds. The maximum response of the filter banks is then selected as the feature image. The fold centers are then identified based on local maxima and thresholding on the feature image. Connecting the fold centers yields a path of the folds. Teniae coli are extracted as lines running between the fold paths. The authors used the spatial relationship between ileocecal valve (ICV) and teniae mesocolica (TM) to identify the TM, then the teniae omentalis (TO) and the teniae libera (TL) can be identified subsequently. Results: The authors tested the proposed method on 47 cases of 37 patients, 10 of the patients with both supine and prone CT scans. The proposed method yielded performance with an average normalized root mean square error (RMSE) ( 6 standard deviation [95% confidence interval]) of 4.87% ( 6 2.93%, [4.05% 5.69%]). Conclusions: The proposed fully-automated teniae coli detection and identification method is accurate and promising for future clinical applications.

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Section: Discussionmentioning

confidence: 99%

Automated teniae coli detection and identification on computed tomographic colonography

et al. 2012

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“…More recently, the taenia coli (three bands of smooth muscle along the colon surface) have been used as features which can be correlated between the two scans [15, 16]. This relies on a manual identification of one of the three taenia coli, and then an automatic algorithm repeats the line representing the identified taenia coli at equal distances.…”

Section: Related Workmentioning

confidence: 99%

“…Similar to reported approaches [4, 20], we identify the taenia coli by detecting the haustral folds, which are computed initially by using the heat diffusion and fuzzy C-means clustering algorithms [20]. Using these haustral folds, we extract the taenia omentalis and the other two taenia coli [15]. Although we extract all the three bands of taenia coli, we mostly use the taenia omentalis for subsequent processing.…”

Section: Computational Algorithmsmentioning

confidence: 99%

Supine and Prone Colon Registration Using Quasi-Conformal Mapping

Zeng

Marino

Gurijala

et al. 2010

IEEE Trans. Visual. Comput. Graphics

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In virtual colonoscopy, CT scans are typically acquired with the patient in both supine (facing up) and prone (facing down) positions. The registration of these two scans is desirable so that the user (physician) can clarify situations or confirm polyp findings at a location in one scan with the same location in the other, thereby improving polyp detection rates and reducing false positives. However, this supine-prone registration is challenging because of the substantial distortions in the colon shape due to the patient’s position shifting. We present an efficient algorithm and framework for performing this registration through the use of conformal geometry to guarantee the registration is a diffeomorphism (a one-to-one and onto mapping). The taenia coli and colon flexures are automatically extracted for each supine and prone surface employing the colon geometry. The two colon surfaces are divided into several segments using the flexures. Each of the colon segments is conformally flattened to the rectangular domain using holomorphic differentials with the taenia coli. For both, the mean curvature are color encoded as texture images, from which feature points are automatically detected using graph cut segmentation, mathematic morphological operations, and principal component analysis. Using these corresponding features, the conformal flattening is adjusted to be quasi-conformal such that the features become aligned. We demonstrate the efficiency and efficacy of our registration method by illustrating matched views on both the 2D flattened colon images and in the 3D volume rendered colon interior view. We evaluate the correctness of the results by measuring the distance between features on the registered colons.

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“…A possible positioning technique that is being developed uses the three smooth muscle bands that run longitudinally along the colon wall, the teniae coli (74). Identification of the teniae coli can allow for a centerline to be computed and a circumferential position of the polyp in the colon to be identified.…”

Section: Future Improvements In Cadmentioning

confidence: 99%

Current Status of CT Colonography

Frentz¹,

Summers²

2006

Academic Radiology

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In 2006, over 55,000 Americans are expected to die of colorectal cancer (CRC) (1). It is estimated that there is over a 5% chance that an American will develop CRC in their lifetime and over a 2% chance that an American will die from CRC (2). Fortunately, in most cases, controlling CRC is possible with the proper screening methods and the subsequent removal of suspicious polyps, adenomas, and carcinomas. If CRC is detected at an early stage, the 5-year survival rate is 90%. Unfortunately, less than 40% of colorectal cancers are detected at an early stage. Once the cancer has developed distant metastases, the 5-year survival rate is less than 10% (2).From 1998 to 2002, the incidence rate of CRC decreased by 1.8% per year, which is believed to have occurred due to increased awareness of the importance of CRC screening and consequent polyp removal (2). However, CRC is still predicted to cause about 10% of all cancer-related deaths in the United States in 2006. Relatively accurate screening methods are available to patients, but patient participation in CRC screening continues to be low. Computed tomography colonography (CTC) is a relatively new screening technology that aims to achieve a high patient acceptance, diagnostic accuracy, and screening effectiveness thereby decreasing mortality rates due to CRC.

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Teniae Coli Guided Navigation and Registration for Virtual Colonoscopy

Cited by 22 publications

References 21 publications

Automated teniae coli detection and identification on computed tomographic colonography

Automated teniae coli detection and identification on computed tomographic colonography

Supine and Prone Colon Registration Using Quasi-Conformal Mapping

Current Status of CT Colonography

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