Biomedical subjects

Homero Schiabel

Publications and source records attributed to Homero Schiabel.

6 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

A segmentation technique to detect masses in dense breast digitized mammograms.

This article describes a segmentation technique that uses the watershed transformation to provide mass detection in dense breast digitized images. The technique consists of four steps: preprocessing, which isolates the breast from the image background; histogram equalization to enhance the contrast; watershed transformation, which calculates the gradient for the whole image; and a topography technique that organizes the segmented parts. We processed 109 regions of interest extracted from mammograms. Preliminary results showed 20% false positive and 85.4% true positive detection regarding the equalized images containing masses. Good results were obtained with this technique. However, additional techniques should be developed to eliminate noise in some images. This technique could be an important tool in mammography.

Breast Neoplasms↗

PubMed2002

Computer technique for digital radiographic images correction based on the digitizer characteristic curve.

This article presents a computer correction technique for radiographic digital images based on digitization process inaccuracy in pixel gray levels relative to the respective image optical densities. The technique consists of determining the digitizer characteristic curve by digitizing a step-wedge radiographic image with known optical densities. Calibration is done by determining the mathematical function that automatically adjusts the pixel gray levels to the expected values according to the manufacturer. Two laser film digitizers were investigated for which discrepancies between measured and expected pixel values were reported. For these cases, the proposed algorithm automatically adjusted the pixel gray levels of the digitized images. Using this method, the digital images show more accurate values of gray levels compared to the original radiographic image. In addition, it allows the development of uniform images databases.

Image Processing, Computer-Assisted↗

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↗

PubMedDate not supplied

Reproducibility of pixel values for two photostimulable phosphor plates in consecutive standardized scannings.

The objective of the present study was to determine the reproducibility of the pixel values obtained with the Digora system (Soredex, Finland). Exposures were standardized, with variation in exposure and scanning time of two photostimulable phosphor plates containing a stepwedge image. The smallest variation in pixel values ranged from 50 to 75%, with the widest variations being observed in less dense steps. A significant difference in pixel values was observed in terms of X-ray exposure and scanning times and between the two plates themselves (ANOVA, p < 0.01). Using the present methodology, the reproducibility of pixel values was not satisfactory for the tested white photostimulable plates. This wide variation in digitalization might be influenced by the amount of X-rays that sensitized the plates. It may be important to establish the reproducibility of the pixel values in quantitative studies using digital image.

Analysis of Variance↗