Wyniki wyszukiwania - BazTech

1

Multiscale modeling of local directional mammogram findings

Jasionowska M, Przelaskowski A.

Journal of Medical Informatics & Technologies

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2011

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Vol. 17

183--190

EN

In this paper two multiresolution transforms (discrete 2D wavelets and complex wavelets) are compared for their capabilities to enhance local texture orientation of mammograms. The local orientation of image texture is useful feature to detect one of the typical types of abnormal findings in mammography - architectural distortions. Our research was directed to define an effective, more reliable directional model of local directional findings in mammograms. Computer-aided diagnosis was considered as a concept of accurate model application.

2

Analysis of suspicious lesions in digital mammograms

Choraś R. S.

Journal of Medical Informatics & Technologies

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2011

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Vol. 17

151--158

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.

3

Adaptive wavelet techniques for compressing digital mammograms

Bruckmann A., Flatscher H., Schell T., Uhl A.

TASK Quarterly : scientific bulletin of Academic Computer Centre in Gdansk

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1999

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Vol. 3, No 4

381-396

EN

In this work we investigate the possible benefit of employing adaptive wavelet algorithms instead of the classical fixed pyramidal wavelet decomposition for the compression of digital mammograms. In particular, we target on adaptive wavelet packet and NSMRA decompositions. We observe that information cost function optimized wavelet packet subband structures do not offer compression performance gain in this case whereas NSMRA decompositions moderately improve the results of classical wavelet decompositions. Due to the lack of fast and reliable search algorithms fixed NSMRA decompositions need to be generated and employed for classes of similar images.

4

Morphological method for extraction of microcalcifications in mammograms for breast cancer diagnosis

Nieniewski M.

Machine Graphics and Vision

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1999

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Vol. 8, No. 3

427-448

EN

The paper presents a new morphological method for extraction of microcalcifications in mammograms for breast cancer diagnosis. The proposed method is based on the use of the morphological detector together with morphological pyramid for detection of local irregularities of brightness in a wide range of size and shapes. The binary maps obtained from the pyramid indicate locations of the condidates for microcalcifications in the mammogram. Independently, the gray level reconstruction of the original mammogram is carried out in order to obtain the axact shape of h-domes, which depic regional maxima (hills) of brithness in the image. By thresholding the image of h-domes, one obtains a binary map of h-domes. Subsequently, a bimary reconstruction is carried out, in which the binary map of h-domes is used as a mask, and the map obtained from the pyramid after some modification is used as the marker. As a result of the reconstruction, the required map of microcalcifications is extracted. A number of tests of the proposed method on various mammograms are presented.