Literature DB >> 8675421

Evaluation of selected two-dimensional segmentation techniques for computed tomography quantitation of lymph nodes.

J Rogowska1, K Batchelder, G S Gazelle, E F Halpern, W Connor, G L Wolf.   

Abstract

RATIONALE AND
OBJECTIVES: As contrast agents that selectively target normal lymph nodes are undergoing development and evaluation, it has become important to accurately and reproducibly determine nodal boundaries to study the agents and determine such values as lymph node area or mean nodal contrast concentration. This study was performed to evaluate the accuracy of different two-dimensional computer segmentation methods, tested on acrylic phantoms constructed to imitate the appearance of lymph nodes surrounded by fat.
METHODS: Five segmentation techniques (manual tracing, semiautomatic local criteria threshold selection, Sobel/watershed technique, interactive deformable contour algorithm and thresholding) were evaluated using phantoms. Subsequently, the first three methods were applied to the images of enhanced lymph nodes in rabbits.
RESULTS: Minimum errors in phantom area measurement (< 5%) and interoperator variation (< 5%) were seen with the Sobel/watershed technique and the interactive deformable contour algorithm. These two techniques were significantly better than thresholding and semiautomated thresholding based on local properties.
CONCLUSION: Methods based on Sobel edge detection offer more objective tools than thresholding methods for segmenting objects similar to lymph nodes in computed tomography images. Both methods, Sobel/watershed and interactive deformable contour algorithm, are fast and have simple user interfaces.

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Year:  1996        PMID: 8675421     DOI: 10.1097/00004424-199603000-00004

Source DB:  PubMed          Journal:  Invest Radiol        ISSN: 0020-9996            Impact factor:   6.016


  5 in total

1.  Complete fully automatic model-based segmentation of normal and pathological lymph nodes in CT data.

Authors:  Lars Dornheim; Jana Dornheim; Ivo Rössling
Journal:  Int J Comput Assist Radiol Surg       Date:  2010-10-08       Impact factor: 2.924

Review 2.  Pediatric obesity phenotyping by magnetic resonance methods.

Authors:  Wei Shen; Haiying Liu; Mark Punyanitya; Jun Chen; Steven B Heymsfield
Journal:  Curr Opin Clin Nutr Metab Care       Date:  2005-11       Impact factor: 4.294

3.  Semiautomatic segmentation of liver metastases on volumetric CT images.

Authors:  Jiayong Yan; Lawrence H Schwartz; Binsheng Zhao
Journal:  Med Phys       Date:  2015-11       Impact factor: 4.071

4.  Mediastinal lymph node detection and station mapping on chest CT using spatial priors and random forest.

Authors:  Jiamin Liu; Joanne Hoffman; Jocelyn Zhao; Jianhua Yao; Le Lu; Lauren Kim; Evrim B Turkbey; Ronald M Summers
Journal:  Med Phys       Date:  2016-07       Impact factor: 4.071

5.  Snake model-based lymphoma segmentation for sequential CT images.

Authors:  Qiang Chen; Fang Quan; Jiajing Xu; Daniel L Rubin
Journal:  Comput Methods Programs Biomed       Date:  2013-06-17       Impact factor: 5.428

  5 in total

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