Comparative assessment of segmentation algorithms for tumor delineation on a test-retest [(11)C]choline dataset.
Med Phys
; 39(12): 7571-9, 2012 Dec.
Article
en En
| MEDLINE
| ID: mdl-23231305
ABSTRACT
PURPOSE:
Many methods have been proposed for tumor segmentation from positron emission tomography images. Because of the increasingly important role that [(11)C]choline is playing in oncology and because no study has compared segmentation methods on this tracer, the authors assessed several segmentation algorithms on a [(11)C]choline test-retest dataset.METHODS:
Fixed and adaptive threshold-based methods, fuzzy C-means (FCM), Canny's edge detection method, the watershed transform, and the fuzzy locally adaptive Bayesian algorithm (FLAB) were used. Test-retest [(11)C]choline scans of nine patients with breast cancer were considered and the percent test-retest variability %VAR(TEST-RETEST) of tumor volume (TV) was employed to assess the results. The same methods were then applied to two denoised datasets generated by applying either a Gaussian filter or the wavelet transform.RESULTS:
The (semi)automated methods FCM, FLAB, and Canny emerged as the best ones in terms of TV reproducibility. For these methods, the %root mean square error %RMSE of %VAR(TEST-RETEST), defined as %RMSE= variance+mean(2), was in the range 10%-21.2%, depending on the dataset and algorithm. Threshold-based methods gave TV estimates which were extremely variable, particularly on the unsmoothed data; their performance improved on the denoised datasets, whereas smoothing did not have a remarkable impact on the (semi)automated methods. TV variability was comparable to that of SUV(MAX) and SUV(MEAN) (range 14.7%-21.9% for %RMSE of %VAR(TEST-RETEST), after the exclusion of one outlier, 40%-43% when the outlier was included).CONCLUSIONS:
The TV variability obtained with the best methods was similar to the one reported for TV in previous [(18)F]FDG and [(18)F]FLT studies and to the one of SUV(MAX)∕SUV(MEAN) on the authors' [(11)C]choline dataset. The good reproducibility of [(11)C]choline TV warrants further studies to test whether TV could predict early response to treatment and survival, as for [(18)F]FDG, to complement∕substitute the use of SUV(MAX) and SUV(MEAN).
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Algoritmos
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Neoplasias de la Mama
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Reconocimiento de Normas Patrones Automatizadas
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Inteligencia Artificial
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Interpretación de Imagen Asistida por Computador
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Colina
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Tomografía de Emisión de Positrones
Tipo de estudio:
Diagnostic_studies
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Evaluation_studies
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Prognostic_studies
Límite:
Female
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Humans
Idioma:
En
Revista:
Med Phys
Año:
2012
Tipo del documento:
Article
País de afiliación:
Reino Unido