Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/43476
Título: Computer-aided measurement of solid breast tumor features on ultrasound images
Autores/as: Alemán-Flores, Miguel 
Aleman-Flores, P 
Alvarez-Leon, L 
Santana-Montesdeoca, José Manuel
Fuentes-Pavon, Rafael
Trujillo-Pino, Agustín 
Clasificación UNESCO: 220990 Tratamiento digital. Imágenes
32 Ciencias médicas
120601 Construcción de algoritmos
120602 Ecuaciones diferenciales
120304 Inteligencia artificial
Palabras clave: Biomineralization
Computer vision
Diagnosis Medical
ImagingTumors
Ultrasonic applications
Fecha de publicación: 2004
Publicación seriada: Lecture Notes in Computer Science 
Conferencia: Workshop on Computer Vision Approaches to Medical Image Analysis (CVAMIA)/Mathematical Methods in Biomedical Image Analysis (MMBIA) held in conjunction with the 8th ECCV
Resumen: This paper presents a new approach in the application of computer vision techniques to the diagnosis of solid breast tumors on ultrasound images. Most works related to medical image analysis for breast cancer detection refer to mammography. However, radiologists have proved the significance of some aspects observed on ultrasound images, among which are spiculation, calcifications, ellipsoid shape, dimensions, echogenicity, capsule, angular margins, lobulations, shadowing and ramifications. We have developed a common framework for the analysis of these criteria, so that a series of parameters are available for the physicians to decide whether the biopsy is necessary or not. We present a set of mathematical methods to extract objective evidence of the presence or absence of the diagnostic criteria. This system is able to extract the relevant features for solid breast nodules with high accuracy and represents a very valuable help in the assessment of radiologists.
URI: http://hdl.handle.net/10553/43476
ISBN: 3-540-22675-3
978-3-540-22675-8
978-3-540-27816-0
ISSN: 0302-9743
DOI: 10.1007/978-3-540-27816-0_30
Fuente: Sonka M., Kakadiaris I.A., Kybic J. (eds) Computer Vision and Mathematical Methods in Medical and Biomedical Image Analysis. MMBIA 2004, CVAMIA 2004. Lecture Notes in Computer Science, vol 3117. Springer, Berlin, Heidelberg
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