Segmentation of Breast Nodules on Ultrasonographic Images Based on Marke d-Controlled Watershed Transform
In this article is presented a computerized segmentation method for breast nodules on ultrasonic images. With the goal of removing the speckle while preserving important information from the lesion boundaries, a Gabor filter followed by an anisotropic diffusion filtering are applied to the ultrasoni...
| Autores: | , , , |
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| Tipo de documento: | artigo |
| Estado: | Versão publicada |
| Data de publicação: | 2010 |
| País: | México |
| Recursos: | Centro de Investigación y de Estudios Avanzados del IPN |
| Repositório: | Redalyc-CINVESTAV |
| OAI Identifier: | oai:redalyc.org:61520234006 |
| Acesso em linha: | https://www.redalyc.org/articulo.oa?id=61520234006 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Computación Segmentation Breast ultrasound Watershed transform Average radial derivative |
| Resumo: | In this article is presented a computerized segmentation method for breast nodules on ultrasonic images. With the goal of removing the speckle while preserving important information from the lesion boundaries, a Gabor filter followed by an anisotropic diffusion filtering are applied to the ultrasonic image. Furthermore, the marker-controlled Watershed transform defines potential boundaries that maximize the Average Radial Derivative function to get the final lesion contour. The segmentation procedure was applied on a database of 50 images and the computer delineated margins were compared against manual outlines drawn by two radiologist. This comparison was performed by two metrics, which measure the similarity between two compared images: overlap ratio (OR) and normalized residual value (nrv). If there is perfect agreement between both images OR = 1 and nrv = 0. Then, the mean values results, for each metric, were for the first radiologist: OR = 0.87¿0.04 and nrv = 0.14¿0.06, and for the second radiologist: OR = 0.86¿0.06 and nrv = 0.15¿0.05. |
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