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Proceedings Paper

Comparative of shape and texture features in classifications of breast masses in digitized mammograms
Author(s): Sergio Koodi Kinoshita; Paulo M. Azevedo Marques; Annie France Frere; Heitor R. C. Marana; Ricardo Jose Ferrari; Roberto Rodrigues Pereira
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Paper Abstract

The aim of this work was to determine a methodology to selection of the best features subset and artificial neural network (ANN) topology to classify masses lesions. The backpropagation training algorithm was used to adjust the weights of ANN. A total of 118 regions of interest images were chosen (68 benign and 50 malignant lesions). In a first step, images were submitted to a combined process of thresholding, mathematical morphology, and region growing techniques. After, fourteen texture features (Haralick descriptors) and fourteen shape features (circularity, compactness, Gupta descriptors, Shen descriptors, Hu descriptors, Fourier descriptor and Wee descriptors) were extracted. The Jeffries-Matusita method was used to select the best features. Three shape features sets and three texture features sets were selected. The Receiver Operating Characteristic (ROC) analyses were conducted to evaluated the classifier performance. The best result for shape feature set was accurate classification rate of 98.21%, specificity of 98.37%, sensitivity of 98.00% and the area under ROC curve of 0.99, for a ANN with 5 hidden units. The best result for texture feature set was accurate classification rate of 97.08%, specificity of 98.53%, sensitivity of 95.11% and the area under ROC curve of 0.98, for an ANN with 4 hidden units.

Paper Details

Date Published: 6 June 2000
PDF: 8 pages
Proc. SPIE 3979, Medical Imaging 2000: Image Processing, (6 June 2000); doi: 10.1117/12.387752
Show Author Affiliations
Sergio Koodi Kinoshita, Univ. of Sao Paulo and Univ. of Marilia (Brazil)
Paulo M. Azevedo Marques, Univ. of Sao Paulo (Brazil)
Annie France Frere, Univ. of Sao Paulo and Univ. of Mogi das Cruzes (Brazil)
Heitor R. C. Marana, Univ. of Sao Paulo (Brazil)
Ricardo Jose Ferrari, Univ. of Sao Paulo (Canada)
Roberto Rodrigues Pereira, Univ. of Sao Paulo (Brazil)

Published in SPIE Proceedings Vol. 3979:
Medical Imaging 2000: Image Processing
Kenneth M. Hanson, Editor(s)

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