2 resultados para Image enhancement
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo
Resumo:
Ultrasonography has an inherent noise pattern, called speckle, which is known to hamper object recognition for both humans and computers. Speckle noise is produced by the mutual interference of a set of scattered wavefronts. Depending on the phase of the wavefronts, the interference may be constructive or destructive, which results in brighter or darker pixels, respectively. We propose a filter that minimizes noise fluctuation while simultaneously preserving local gray level information. It is based on steps to attenuate the destructive and constructive interference present in ultrasound images. This filter, called interference-based speckle filter followed by anisotropic diffusion (ISFAD), was developed to remove speckle texture from B-mode ultrasound images, while preserving the edges and the gray level of the region. The ISFAD performance was compared with 10 other filters. The evaluation was based on their application to images simulated by Field II (developed by Jensen et al.) and the proposed filter presented the greatest structural similarity, 0.95. Functional improvement of the segmentation task was also measured, comparing rates of true positive, false positive and accuracy. Using three different segmentation techniques, ISFAD also presented the best accuracy rate (greater than 90% for structures with well-defined borders). (E-mail: fernando.okara@gmail.com) (C) 2012 World Federation for Ultrasound in Medicine & Biology.
Resumo:
Objective: The purpose of this study was to analyse the use of digital tools for image enhancement of mandibular radiolucent lesions and the effects of this manipulation on the percentage of correct radiographic diagnoses. Methods: 24 panoramic radiographs exhibiting radiolucent lesions were selected, digitized and evaluated by non-experts (undergraduate and newly graduated practitioners) and by professional experts in oral diagnosis. The percentages of correct and incorrect diagnoses, according to the use of brightness/contrast, sharpness, inversion, highlight and zoom tools, were compared. All dental professionals made their evaluations without (T-1) and with (T-2) a list of radiographic diagnostic parameters. Results: Digital tools were used with low frequency mainly in T-2. The most preferred tool was sharpness (45.2%). In the expert group, the percentage of correct diagnoses did not change when any of the digital tools were used. For the non-expert group, there was an increase in the frequency of correct diagnoses when brightness/contrast was used in T-2 (p = 0.008) and when brightness/contrast and sharpness were not used in T-1 (p = 0.027). The use or non-use of brightness/contrast, zoom and sharpness showed moderate agreement in the group of experts [kappa agreement coefficient (kappa) = 0.514, 0.425 and 0.335, respectively]. For the non-expert group there was slight agreement for all the tools used (kappa <= 0.237). Conclusions: Consulting the list of radiographic parameters before image manipulation reduced the frequency of tool use in both groups of examiners. Consulting the radiographic parameters with the use of some digital tools was important for improving correct diagnosis only in the group of non-expert examiners. Dentomaxillofacial Radiology (2012) 41, 203-210. doi: 10.1259/dmfr/78567773