Analysis of suspicious lesions in digital mammograms

• Autorzy: Choraś R. S.
• Języki publikacji: EN

Abstrakty

EN

The system using steerable filters for analysis suspicious lesions in mammograms is proposed. This system is based on moments and texture features. The set of well defined and classified suspicious lesions regions from mammograms database are used as a reference pattern. The similarity measure for reference pattern image and patient mammogram is found by computing the distance between their corresponding feature vectors. The Euclidean distance metric is used to finding the nearest class to patient feature vector what in result mark the automatically classify this mammograms.

Słowa kluczowe

EN

steerable filters; mammograms; moment and texture features; feature extraction; classification

PL

sterowane filtry; mammografie; wychwytywanie cech; klasyfikacja

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2011
• Tom: Vol. 17
• Strony: 151--158
• Opis fizyczny: Bibliogr. 5 poz., rys., tab.

Twórcy

autor

Choraś R. S.

• University of Technology & Life Sciences, Department of Telecommunications & EE, ul. Kaliskiego 7, 85-796 Bydgoszcz

Bibliografia

• [1] JACOB M., UNSER M., Design of steerable filters for feature detection using Canny-like criteria, IEEE Trans. On Pattern Analysis and Machine Intelligence, Vol. 26, No. 8, 2004, pp.1007-1019.
• [2] FREEMAN W.T., ADELSON E.H., The design and use of steerable filters, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 13, No. 9, 1991, pp. 891-906.
• [3] SINGH S., AL-MANSOORI R., Identification of regions of interest in digital mammograms, J. Intell. Systems, Vol. 10, 2000, pp. 183-210.
• [4] LAINE A.F., SCHULER S., FAN J., HUDA W., Mammographic feature enhancement by multiscale analysis, IEEE Transactions on Medical Imaging, Vol. 13, No. 4, 1994, pp. 725–740.
• [5] PEJNOVIC P., BUTUROVIC L., STOJILJKOVIC Z., Object recognition by invariants, Proc. 11th IAPR Int. Conf. On Pattern Recognition, 1992, pp. 434 – 437.