Literature DB >> 16628034

Volumetric analysis of liver metastases in computed tomography with the fuzzy C-means algorithm.

Peter J Yim1, Amit V Vora, Deepak Raghavan, Ravi Prasad, Matthew McAullife, Pamela Ohman-Strickland, John L Nosher.   

Abstract

Tumor size is often determined from computed tomography (CT) images to assess disease progression. A study was conducted to demonstrate the advantages of the fuzzy C-means (FCM) algorithm for volumetric analysis of colorectal liver metastases in comparison with manual contouring. Intra-and interobserver variability was assessed for manual contouring and the FCM algorithm in a study involving contrast-enhanced helical CT images of 43 hypoattenuating liver lesions from 15 patients with a history of colorectal cancer. Measurement accuracy and interscan variability of the FCM and manual methods were assessed in a phantom study using paraffin pseudotumors. In the clinical imaging study, intra-and interobserver variability was reduced using the FCM algorithm as compared with manual contouring (P = 0.0070 and P = 0.0019, respectively). Accuracy of the measurement of the pseudotumor volume was improved using the FCM method as compared with the manual method (P = 0.047). Interscan variability of the pseudotumor volumes was measured using the FCM method as compared with the manual method (P = 0.04). The FCM algorithm volume was highly correlated with the manual contouring volume (r = 0.9997). Finally, the shorter time spent in calculating tumor volume using the FCM method versus the manual contouring method was marginally statistically significant (P = 0.080). These results suggest that the FCM algorithm has substantial advantages over manual contouring for volumetric measurement of colorectal liver metastases from CT.

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Year:  2006        PMID: 16628034     DOI: 10.1097/00004728-200603000-00008

Source DB:  PubMed          Journal:  J Comput Assist Tomogr        ISSN: 0363-8715            Impact factor:   1.826


  9 in total

Review 1.  Imaging diagnosis of colorectal liver metastases.

Authors:  Ling-Hui Xu; San-Jun Cai; Guo-Xiang Cai; Wei-Jun Peng
Journal:  World J Gastroenterol       Date:  2011-11-14       Impact factor: 5.742

2.  Multimodality 3D Tumor Segmentation in HCC Patients Treated with TACE.

Authors:  Zhijun Wang; Julius Chapiro; Rüdiger Schernthaner; Rafael Duran; Rongxin Chen; Jean-François Geschwind; MingDe Lin
Journal:  Acad Radiol       Date:  2015-04-08       Impact factor: 3.173

3.  Liver tumour segmentation using contrast-enhanced multi-detector CT data: performance benchmarking of three semiautomated methods.

Authors:  Jia-Yin Zhou; Damon W K Wong; Feng Ding; Sudhakar K Venkatesh; Qi Tian; Ying-Yi Qi; Wei Xiong; Jimmy J Liu; Wee-Kheng Leow
Journal:  Eur Radiol       Date:  2010-02-16       Impact factor: 5.315

4.  Comparison of two-dimensional and three-dimensional iterative watershed segmentation methods in hepatic tumor volumetrics.

Authors:  Shonket Ray; Rosalie Hagge; Marijo Gillen; Miguel Cerejo; Shidrokh Shakeri; Laurel Beckett; Tamara Greasby; Ramsey D Badawi
Journal:  Med Phys       Date:  2008-12       Impact factor: 4.071

5.  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

6.  Comparison of semi-automatic volumetric VX2 hepatic tumor segmentation from cone beam CT and multi-detector CT with histology in rabbit models.

Authors:  Olivier Pellerin; Mingde Lin; Nikhil Bhagat; Roberto Ardon; Benoit Mory; Jean-François Geschwind
Journal:  Acad Radiol       Date:  2012-09-02       Impact factor: 3.173

7.  Feature-based automated segmentation of ablation zones by fuzzy c-mean clustering during low-dose computed tomography.

Authors:  Po-Hung Wu; Mariajose Bedoya; Jim White; Christopher L Brace
Journal:  Med Phys       Date:  2020-12-18       Impact factor: 4.071

Review 8.  How bioinformatics influences health informatics: usage of biomolecular sequences, expression profiles and automated microscopic image analyses for clinical needs and public health.

Authors:  Vladimir Kuznetsov; Hwee Kuan Lee; Sebastian Maurer-Stroh; Maria Judit Molnár; Sandor Pongor; Birgit Eisenhaber; Frank Eisenhaber
Journal:  Health Inf Sci Syst       Date:  2013-01-10

9.  Radiofrequency ablation of liver tumors: quantitative assessment of tumor coverage through CT image processing.

Authors:  Katia Passera; Sabrina Selvaggi; Davide Scaramuzza; Francesco Garbagnati; Daniele Vergnaghi; Luca Mainardi
Journal:  BMC Med Imaging       Date:  2013-01-16       Impact factor: 1.930

  9 in total

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