The Experts below are selected from a list of 3069 Experts worldwide ranked by ideXlab platform
Yifeng Zhou - One of the best experts on this subject based on the ideXlab platform.
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Generating high Gray-Level Resolution monochrome displays with conventional computer graphics cards and color monitors.
Journal of neuroscience methods, 2003Co-Authors: Jianzhong Jin, Yifeng ZhouAbstract:Display systems based on conventional computer graphics cards are capable of generating images with about 8-bit luminance Resolution. However, most vision experiments require more than 12 bits of luminance Resolution. Pelli and Zhang [Spatial Vis. 10 (1997) 443] described a video attenuator for generating high luminance Resolution displays on a monochrome monitor, or for driving just the green gun of a color monitor. Here we show how to achieve a white display by adding video amplifiers to duplicate the monochrome signal to drive all three guns of any color monitor. Because of the lack of the availability of high quality monochrome monitors, our method provides an inexpensive way to achieve high-Resolution monochromatic displays using conventional, easy-to-get equipment. We describe the design principles, test results, and a few additional functionalities.
Jianzhong Jin - One of the best experts on this subject based on the ideXlab platform.
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Generating high Gray-Level Resolution monochrome displays with conventional computer graphics cards and color monitors.
Journal of neuroscience methods, 2003Co-Authors: Jianzhong Jin, Yifeng ZhouAbstract:Display systems based on conventional computer graphics cards are capable of generating images with about 8-bit luminance Resolution. However, most vision experiments require more than 12 bits of luminance Resolution. Pelli and Zhang [Spatial Vis. 10 (1997) 443] described a video attenuator for generating high luminance Resolution displays on a monochrome monitor, or for driving just the green gun of a color monitor. Here we show how to achieve a white display by adding video amplifiers to duplicate the monochrome signal to drive all three guns of any color monitor. Because of the lack of the availability of high quality monochrome monitors, our method provides an inexpensive way to achieve high-Resolution monochromatic displays using conventional, easy-to-get equipment. We describe the design principles, test results, and a few additional functionalities.
Omar Schiaratura - One of the best experts on this subject based on the ideXlab platform.
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Preliminary results of a featureless CAD system on FFDM images
2014Co-Authors: Renato Campanini, Enrico Angelini, Danilo Dongiovanni, Emiro Iampieri, Claude Mair-noack, Matteo Masotti, Matteo Roffilli, Gianni Saguatti, Omar SchiaraturaAbstract:Abstract. A novel featureless approach to the detection of masses and microcalcifications has been adopted, based on a Support Vector Machine (SVM) classifier. This method does not rely on any feature extraction task; on the contrary, the algorithm automatically learns to detect the lesions by the examples presented to it during the training phase. Our technique includes a pre-selection step, in which we select the intra-breast areas that will be analyzed. Those regions are then provided to an SVM classifier, trained to recognize suspect masses or microcalcifications. The CAD performance have been already assessed on digitized mammogram freely available on the net (DDSM USF and Nijmegen databases). In this paper we are going to test the CAD scheme on digital images coming from Giotto Image MD FFDM unit, a mammography system based on an amorphous Selenium detector. Images have a spatial Resolution equal to 85 um and 13 bit Gray-Level Resolution and have been collected at two different sites: Maggiore Hospital in Bologna (Italy) and Triemli Hospital in Zurich (Switzerland). Preliminary results are presented on a database gathered at these hospitals. The CAD system marked in the FFDM images 19 cancers out of 23, with a false-positive rate of 0.9 marks per image. 1
Siegfried Wahl - One of the best experts on this subject based on the ideXlab platform.
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tuebingencstest a useful method to assess the contrast sensitivity function
Biomedical Optics Express, 2017Co-Authors: Tim Schilling, Arne Ohlendorf, Alexander Leube, Siegfried WahlAbstract:Since contrast sensitivity (CS) relies on the accuracy of stimulus presentation, the reliability of the psychophysical procedure and observer’s attention, the measurement of the CS-function is critical and therefore, a useful threshold contrast measurement was developed. The Tuebingen Contrast Sensitivity Test (TueCST) includes an adaptive staircase procedure and a 16-bit Gray-Level Resolution. In order to validate the CS measurements with the TueCST, measurements were compared with existing tests by inter-test repeatability, test-retest reliability and time. The novel design enables an accurate presentation of the spatial frequency and higher precision, inter-test repeatability and test-retest reliability compared to other existing tests.
Renato Campanini - One of the best experts on this subject based on the ideXlab platform.
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Preliminary results of a featureless CAD system on FFDM images
2014Co-Authors: Renato Campanini, Enrico Angelini, Danilo Dongiovanni, Emiro Iampieri, Claude Mair-noack, Matteo Masotti, Matteo Roffilli, Gianni Saguatti, Omar SchiaraturaAbstract:Abstract. A novel featureless approach to the detection of masses and microcalcifications has been adopted, based on a Support Vector Machine (SVM) classifier. This method does not rely on any feature extraction task; on the contrary, the algorithm automatically learns to detect the lesions by the examples presented to it during the training phase. Our technique includes a pre-selection step, in which we select the intra-breast areas that will be analyzed. Those regions are then provided to an SVM classifier, trained to recognize suspect masses or microcalcifications. The CAD performance have been already assessed on digitized mammogram freely available on the net (DDSM USF and Nijmegen databases). In this paper we are going to test the CAD scheme on digital images coming from Giotto Image MD FFDM unit, a mammography system based on an amorphous Selenium detector. Images have a spatial Resolution equal to 85 um and 13 bit Gray-Level Resolution and have been collected at two different sites: Maggiore Hospital in Bologna (Italy) and Triemli Hospital in Zurich (Switzerland). Preliminary results are presented on a database gathered at these hospitals. The CAD system marked in the FFDM images 19 cancers out of 23, with a false-positive rate of 0.9 marks per image. 1
