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Use of fractals in determining the malignancy degree of lung nodules.
Amador-Legon, Noel Victor; Perez-Diaz, Marlen.
Afiliação
  • Amador-Legon NV; Laboratory of Image Processing, Automatic Department, Universidad Central "Marta Abreu" de las Villas, Santa Clara, Cuba.
  • Perez-Diaz M; Laboratory of Image Processing, Automatic Department, Universidad Central "Marta Abreu" de las Villas, Santa Clara, Cuba.
Front Med Technol ; 6: 1362688, 2024.
Article em En | MEDLINE | ID: mdl-38595696
ABSTRACT

Introduction:

A Computer-Assisted Detection (CAD) System for classification into malignant-benign classes using CT images is proposed.

Methods:

Two methods that use the fractal dimension (FD) as a measure of the lung nodule contour irregularities (Box counting and Power spectrum) were implemented. The LIDC-IDRI database was used for this study. Of these, 100 slices belonging to 100 patients were analyzed with both methods.

Results:

The performance between both methods was similar with an accuracy higher than 90%. Little overlap was obtained between FD ranges for the different malignancy grades with both methods, being slightly better in Power spectrum. Box counting had one more false positive than Power spectrum.

Discussion:

Both methods are able to establish a boundary between the high and low malignancy degree. To further validate these results and enhance the performance of the CAD system, additional studies will be necessary.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Med Technol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Cuba País de publicação: Suíça

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Med Technol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Cuba País de publicação: Suíça