Abstract

Electronic cleansing is an image post processing technique in which the tagged colonic content is subtracted from colon using CTC images. There are post processing artefacts, like: 1) soft tissue degradation; 2) incomplete cleansing; 3) misclassification of polyp due to pseudo enhanced voxels; and 4) pseudo soft tissue structures. The objective of the study was to subtract the tagged colonic content without losing the soft tissue structures. This paper proposes a novel adaptive method to solve the first three problems using a multi-step algorithm. It uses a new edge model-based method which involves colon segmentation, priori information of Hounsfield units (HU) of different colonic contents at specific tube voltages, subtracting the tagging materials, restoring the soft tissue structures based on selective HU, removing boundary between air-contrast, and applying a filter to clean minute particles due to improperly tagged endoluminal fluids which appear as noise. The main finding of the study was submerged soft tissue structures were absolutely preserved and the pseudo enhanced intensities were corrected without any artifact. The method was implemented with multithreading for parallel processing in a high performance computer. The technique was applied on a fecal tagged dataset (30 patients) where the tagging agent was not completely removed from colon. The results were then qualitatively validated by radiologists for any image processing artifacts.

Original languageEnglish
Pages (from-to)8351-8358
Number of pages8
JournalAsian Pacific Journal of Cancer Prevention
Volume16
Issue number18
DOIs
Publication statusPublished - 2016

Fingerprint

Tomography
Artifacts
Colon
Post and Core Technique
Proxy
Polyps
Noise
Air

All Science Journal Classification (ASJC) codes

  • Epidemiology
  • Oncology
  • Public Health, Environmental and Occupational Health
  • Cancer Research

Cite this

@article{c829f8dcb8d046c5826db4f3e97279ba,
title = "Automatic electronic cleansing in computed tomography colonography images using domain knowledge",
abstract = "Electronic cleansing is an image post processing technique in which the tagged colonic content is subtracted from colon using CTC images. There are post processing artefacts, like: 1) soft tissue degradation; 2) incomplete cleansing; 3) misclassification of polyp due to pseudo enhanced voxels; and 4) pseudo soft tissue structures. The objective of the study was to subtract the tagged colonic content without losing the soft tissue structures. This paper proposes a novel adaptive method to solve the first three problems using a multi-step algorithm. It uses a new edge model-based method which involves colon segmentation, priori information of Hounsfield units (HU) of different colonic contents at specific tube voltages, subtracting the tagging materials, restoring the soft tissue structures based on selective HU, removing boundary between air-contrast, and applying a filter to clean minute particles due to improperly tagged endoluminal fluids which appear as noise. The main finding of the study was submerged soft tissue structures were absolutely preserved and the pseudo enhanced intensities were corrected without any artifact. The method was implemented with multithreading for parallel processing in a high performance computer. The technique was applied on a fecal tagged dataset (30 patients) where the tagging agent was not completely removed from colon. The results were then qualitatively validated by radiologists for any image processing artifacts.",
author = "Manjunath, {K. N.} and Siddalingaswamy, {P. C.} and Prabhu, {G. K.}",
year = "2016",
doi = "10.7314/APJCP.2015.16.18.8351",
language = "English",
volume = "16",
pages = "8351--8358",
journal = "Asian Pacific Journal of Cancer Prevention",
issn = "1513-7368",
publisher = "Asian Pacific Organization for Cancer Prevention",
number = "18",

}

TY - JOUR

T1 - Automatic electronic cleansing in computed tomography colonography images using domain knowledge

AU - Manjunath, K. N.

AU - Siddalingaswamy, P. C.

AU - Prabhu, G. K.

PY - 2016

Y1 - 2016

N2 - Electronic cleansing is an image post processing technique in which the tagged colonic content is subtracted from colon using CTC images. There are post processing artefacts, like: 1) soft tissue degradation; 2) incomplete cleansing; 3) misclassification of polyp due to pseudo enhanced voxels; and 4) pseudo soft tissue structures. The objective of the study was to subtract the tagged colonic content without losing the soft tissue structures. This paper proposes a novel adaptive method to solve the first three problems using a multi-step algorithm. It uses a new edge model-based method which involves colon segmentation, priori information of Hounsfield units (HU) of different colonic contents at specific tube voltages, subtracting the tagging materials, restoring the soft tissue structures based on selective HU, removing boundary between air-contrast, and applying a filter to clean minute particles due to improperly tagged endoluminal fluids which appear as noise. The main finding of the study was submerged soft tissue structures were absolutely preserved and the pseudo enhanced intensities were corrected without any artifact. The method was implemented with multithreading for parallel processing in a high performance computer. The technique was applied on a fecal tagged dataset (30 patients) where the tagging agent was not completely removed from colon. The results were then qualitatively validated by radiologists for any image processing artifacts.

AB - Electronic cleansing is an image post processing technique in which the tagged colonic content is subtracted from colon using CTC images. There are post processing artefacts, like: 1) soft tissue degradation; 2) incomplete cleansing; 3) misclassification of polyp due to pseudo enhanced voxels; and 4) pseudo soft tissue structures. The objective of the study was to subtract the tagged colonic content without losing the soft tissue structures. This paper proposes a novel adaptive method to solve the first three problems using a multi-step algorithm. It uses a new edge model-based method which involves colon segmentation, priori information of Hounsfield units (HU) of different colonic contents at specific tube voltages, subtracting the tagging materials, restoring the soft tissue structures based on selective HU, removing boundary between air-contrast, and applying a filter to clean minute particles due to improperly tagged endoluminal fluids which appear as noise. The main finding of the study was submerged soft tissue structures were absolutely preserved and the pseudo enhanced intensities were corrected without any artifact. The method was implemented with multithreading for parallel processing in a high performance computer. The technique was applied on a fecal tagged dataset (30 patients) where the tagging agent was not completely removed from colon. The results were then qualitatively validated by radiologists for any image processing artifacts.

UR - http://www.scopus.com/inward/record.url?scp=84954287650&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84954287650&partnerID=8YFLogxK

U2 - 10.7314/APJCP.2015.16.18.8351

DO - 10.7314/APJCP.2015.16.18.8351

M3 - Article

VL - 16

SP - 8351

EP - 8358

JO - Asian Pacific Journal of Cancer Prevention

JF - Asian Pacific Journal of Cancer Prevention

SN - 1513-7368

IS - 18

ER -