Computer aided system for segmentation and visualization of microcalcifications in digital mammograms.

Two methods for segmentation and visualization of microcalcifications in digital or digitized mammograms are described. First method is based on modern mathematical morphology, while the second one uses the multifractal approach. In the first method, by using an appropriate combination of some morphological operations, high local contrast enhancement, followed by significant suppression of background tissue, irrespective of its radiology density, is obtained. By iterative procedure, this method highly emphasizes only small bright details, possible microcalcifications. In a multifractal approach, from initial mammogram image, a corresponding multifractal "images" are created, from which a radiologist has a freedom to change the level of segmentation. An appropriate user friendly computer aided visualization (CAV) system with embedded two methods is realized. The interactive approach enables the physician to control the level and the quality of segmentation. Suggested methods were tested through mammograms from MIAS database as a gold standard, and from clinical praxis, using digitized films and digital images from full field digital mammograph

Enhancement of microcalcifications in digitized mammograms: Multifractal and mathematical morphology approach

Prikazana su dva metoda isticanja mikrokalcifikacija u digitalnim mamogramima. Prvi metod zasnovan je na multifraktalnoj analizi digitalne slike, a drugi na primeni moderne matematičke morfologije. U multifraktalnom pristupu kreiraju se multifraktalne 'slike' izvornog mamograma, na osnovu kojih se dalje interaktivno bira nivo segmentacije detalja. Drugi metod, pogodnom kombinacijom morfoloških operacija, povećava lokalni kontrast uz snažno potiskivanje pozadinske teksture, nezavisno od radiološke gustine tkiva dojke. Iterativnim postupkom morfološki metod visoko ističe samo male detalje sjajnije od okolnog tkiva, potencijalne mikrokalcifikacije. Interaktivni pristup kod oba metoda omogućava radiologu da kontroliše nivo izdvajanja detalja. Predloženi metodi su testirani na referentnim mamogramima iz miniMIAS baze i iz kliničke prakse.Two methods for enhancing the microcalcifications in digitized mammograms are under consideration. First method is based on multifractal approach, and second on modern mathematical morphology. In multifractal approach, from initial mammogram image, a corresponding multifractal 'images' are created, from which a radiologist has a freedom to change the level of segmentation in an interactive manner. The second method, using an appropriate combination of some morphological operations, enables high local contrast enhancement, followed by significant suppression of background tissue, irrespective of the radiology density of the tissue. By iterative procedure this method highly emphasizes only small bright details, possible microcalcifications. The interactive approach enables the physician to control the level of segmentation. Suggested methods were tested through referent mammograms from MiniMIAS database and from clinical praxis mammograms

Computer aided system for segmentation and visualization of microcalcifications in digital mammograms

Two methods for segmentation and visualization of microcalcifications in digital or digitized mammograms are described. First method is based on modern mathematical morphology, while the second one uses the multifractal approach. In the first method, by using an appropriate combination of some morphological operations, high local contrast enhancement, followed by significant suppression of background tissue, irrespective of its radiology density, is obtained. By iterative procedure, this method highly emphasizes only small bright details, possible microcalcifications. In a multifractal approach, from initial mammogram image, a corresponding multifractal "images" are created, from which a radiologist has a freedom to change the level of segmentation. An appropriate user friendly computer aided visualization (CAV) system with embedded two methods is realized. The interactive approach enables the physician to control the level and the quality of segmentation. Suggested methods were tested through mammograms from MIAS database as a gold standard, and from clinical praxis, using digitized films and digital images from full field digital mammograph

Fractal geometry and multifractals in analyzing and processing medical data and images

A traditional way for describing objects, based on the well-known Euclidean geometry, is not capable to describe different natural objects and phenomena such as clouds, relief shapes, trends in economy, etc. On the contrary fractal geometry and its extension multifractals are new "tools" which can be used for describing, modeling, analyzing and processing different complex shapes and signals. This paper considers fractal geometry and multifractals and their application in signal analyzing and processing particularly in medical signal analysis