Biomedical subjects

Fátima L S Nunes

Publications and source records attributed to Fátima L S Nunes.

3 recordsLinked to original sources

PubMed2007

Contrast enhancement in dense breast images to aid clustered microcalcifications detection.

This paper presents a method to provide contrast enhancement in dense breast digitized images, which are difficult cases in testing of computer-aided diagnosis (CAD) schemes. Three techniques were developed, and data from each method were combined to provide a better result in relation to detection of clustered microcalcifications. Results obtained during the tests indicated that, by combining all the developed techniques, it is possible to improve the performance of a processing scheme designed to detect microcalcification clusters. It also allows operators to distinguish some of these structures in low-contrast images, which were not detected via conventional processing before the contrast enhancement. This investigation shows the possibility of improving CAD schemes for better detection of microcalcifications in dense breast images.

Breast Neoplasms↗

PubMed2002

Evaluation of microcalcifications segmentation techniques for dense breast digitized images.

Some processing techniques cited in the literature used for microcalcifications detection in digitized mammograms are evaluated here with regard to dense breast images. Three techniques were investigated: Nappi et al.'s, Nishikawa et al.'s and Wallet et al.'s. The methods were tested with low-contrast phantom images, simulating dense breast images. The ability of each technique to detect microcalcifications in dense breast images was evaluated. The following detection rates were obtained: Nappi et al's technique, 78.3%; Wallet et al.'s, 86.6%; and Nishikawa et al.'s, 94.4%. Dense breast images affect the performance of CAD schemes, as confirmed by our results. Therefore, data from those segmentation techniques applied to dense breast images could be improved by developing a hybrid method using the best characteristics of each technique.

Calcinosis↗

PubMed2002

Contrast enhancement in dense breast images using the modulation transfer function.

This work proposes a method aimed at enhancing the contrast in dense breast images in mammography. It includes a new preprocessing technique, which uses information on the modulation transfer function (MTF) of the mammographic system in the whole radiation field. The method is applied to improve the efficiency of a computer-aided diagnosis (CAD) scheme. Seventy-five regions of interest (ROIs) from dense mammograms were acquired in two pieces of equipment (a CGR Senographe 500t and a Philips Mammodiagnost) and were digitized in a Lumiscan 50 laser scanner. A computational procedure determines the effective focal spot size in each region of interest from the measured focal spot in the center for a given mammographic equipment. Using computational simulation the MTF is then calculated for each field region. A procedure that enlarges the high-frequency portion of this function is applied and a convolution between the resulting new function and the original image is performed. Both original and enhanced images were submitted to a processing procedure for detecting clustered microcalcifications in order to compare the performance for dense breast images. ROIs were divided into four groups, two for each piece of equipment-one with clustered microcalcifications and another without microcalcifications. Our results show that in about 10% of the enhanced images more signals were detected when compared to the results for the original dense breast images. This is important because the usual processing techniques used in CAD schemes present poor results when applied to dense breast images. Since the MTF method is a well-recognized tool in the evaluation of radiographic systems, this new technique could be used to associate quality assurance procedures with the processing schemes employed in CAD for mammography.

False Negative Reactions↗