Literature DB >> 21762887

A straightforward approach to computer-aided polyp detection using a polyp-specific volumetric feature in CT colonography.

June-Goo Lee1, Jong Hyo Kim, Se Hyung Kim, Hee Sun Park, Byung Ihn Choi.   

Abstract

This study presents a straightforward approach to computer-aided polyp detection and explores its advantages and future potential. A straightforward computer-aided polyp detection (CAD) scheme was developed that consisted of colon wall segmentation, a polyp-specific volumetric filter, and the counting and thresholding of cluster volume sizes. 65 patients had undergone the bowel cleaning scheme without fecal tagging and the optical colonoscopy (OC) and CT colonography (CTC) were performed. The polyp sizes determined by OC were used as reference measurements. The CTC dataset with 103 polyps were divided into training and test datasets. After tuning for the optimal parameter settings, the per-polyp sensitivities of the developed CAD scheme for clinically relevant polyps (≥ 6 mm) were 100% at 8.5 false positives (FPs)/patient using the training dataset, and 93.3% at 7.7 FPs/patient using the test dataset. The developed CAD scheme was found to have a relatively high detection performance, easily optimized parameter settings, and an easily understood internal operation.
Copyright © 2011 Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 21762887     DOI: 10.1016/j.compbiomed.2011.06.015

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  5 in total

1.  Fully automated segmentation of cartilage from the MR images of knee using a multi-atlas and local structural analysis method.

Authors:  June-Goo Lee; Serter Gumus; Chan Hong Moon; C Kent Kwoh; Kyongtae Ty Bae
Journal:  Med Phys       Date:  2014-09       Impact factor: 4.071

2.  A Systematic Approach of Data Collection and Analysis in Medical Imaging Research.

Authors:  Manjunath K N; Chitra Manuel; Govardhan Hegde; Anjali Kulkarni; Rajendra Kurady; Manuel K
Journal:  Asian Pac J Cancer Prev       Date:  2021-02-01

3.  Measurement of smaller colon polyp in CT colonography images using morphological image processing.

Authors:  K N Manjunath; P C Siddalingaswamy; G K Prabhu
Journal:  Int J Comput Assist Radiol Surg       Date:  2017-06-01       Impact factor: 2.924

4.  Rapid Polyp Classification in Colonoscopy Using Textural and Convolutional Features.

Authors:  Chung-Ming Lo; Yu-Hsuan Yeh; Jui-Hsiang Tang; Chun-Chao Chang; Hsing-Jung Yeh
Journal:  Healthcare (Basel)       Date:  2022-08-08

Review 5.  Development of artificial intelligence technology in diagnosis, treatment, and prognosis of colorectal cancer.

Authors:  Feng Liang; Shu Wang; Kai Zhang; Tong-Jun Liu; Jian-Nan Li
Journal:  World J Gastrointest Oncol       Date:  2022-01-15
  5 in total

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