Literature DB >> 20172789

Electronic cleansing for computed tomography (CT) colonography using a scale-invariant three-material model.

Iwo W O Serlie1, Frans M Vos, Roel Truyen, Frits H Post, Jaap Stoker, Lucas J van Vliet.   

Abstract

A well-known reading pitfall in computed tomography (CT) colonography is posed by artifacts at T-junctions, i.e., locations where air-fluid levels interface with the colon wall. This paper presents a scale-invariant method to determine material fractions in voxels near such T-junctions. The proposed electronic cleansing method particularly improves the segmentation at those locations. The algorithm takes a vector of Gaussian derivatives as input features. The measured features are made invariant to the orientation-dependent apparent scale of the data and normalized in a way to obtain equal noise variance. A so-called parachute model is introduced that maps Gaussian derivatives onto material fractions near T-junctions. Projection of the noisy derivatives onto the model yields improved estimates of the true, underlying feature values. The method is shown to render an accurate representation of the object boundary without artifacts near junctions. Therefore, it enhances the reading of CT colonography in a 3-D display mode.

Mesh:

Year:  2010        PMID: 20172789     DOI: 10.1109/TBME.2010.2040280

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  6 in total

1.  Automated image-based colon cleansing for laxative-free CT colonography computer-aided polyp detection.

Authors:  Marius George Linguraru; Neil Panjwani; Joel G Fletcher; Ronald M Summers
Journal:  Med Phys       Date:  2011-12       Impact factor: 4.071

2.  Electronic cleansing for dual-energy CT colonography based on material decomposition and virtual monochromatic imaging.

Authors:  Rie Tachibana; Janne J Näppi; Se Hyung Kim; Hiroyuki Yoshida
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2015-03-20

3.  Mosaic decomposition: an electronic cleansing method for inhomogeneously tagged regions in noncathartic CT colonography.

Authors:  Wenli Cai; June-Goo Lee; Michael E Zalis; Hiroyuki Yoshida
Journal:  IEEE Trans Med Imaging       Date:  2010-10-14       Impact factor: 10.048

Review 4.  Deep Learning Electronic Cleansing for Single- and Dual-Energy CT Colonography.

Authors:  Rie Tachibana; Janne J Näppi; Junko Ota; Nadja Kohlhase; Toru Hironaka; Se Hyung Kim; Daniele Regge; Hiroyuki Yoshida
Journal:  Radiographics       Date:  2018 Nov-Dec       Impact factor: 6.312

5.  Electronic cleansing in computed tomography colonography using AT layer identification with integration of gradient directional second derivative and material fraction model.

Authors:  Krisorn Chunhapongpipat; Ratinan Boonklurb; Bundit Chaopathomkul; Sirod Sirisup; Rajalida Lipikorn
Journal:  BMC Med Imaging       Date:  2017-09-04       Impact factor: 1.930

6.  Self-Supervised Adversarial Learning with a Limited Dataset for Electronic Cleansing in Computed Tomographic Colonography: A Preliminary Feasibility Study.

Authors:  Rie Tachibana; Janne J Näppi; Toru Hironaka; Hiroyuki Yoshida
Journal:  Cancers (Basel)       Date:  2022-08-26       Impact factor: 6.575

  6 in total

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