Matching methods evaluation framework for stereoscopic breast

Three-dimensional (3-D) imaging has been intensively studied in the past few decades. Depth information is an important added value of 3-D systems over two-dimensional systems. Special focuses were devoted to the development of stereo matching methods for the generation of disparity maps (i.e., depth information within a 3-D scene). Dedicated frameworks were designed to evaluate and rank the performance of different stereo matching methods but never considering x-ray medical images. Yet, 3-D x-ray acquisition systems and 3-D medical displays have already been introduced into the diagnostic market. To access the depth information within x-ray stereoscopic images, computing accurate disparity maps is essential. We aimed at developing a framework dedicated to x-ray stereoscopic breast images used to evaluate and rank several stereo matching methods. A multiresolution pyramid optimization approach was integrated to the framework to increase the accuracy and the efficiency of the stereo matching techniques. Finally, a metric was designed to score the results of the stereo matching compared with the ground truth. Eight methods were evaluated and four of them [locally scaled sum of absolute differences (LSAD), zero mean sum of absolute differences, zero mean sum of squared differences, and locally scaled mean sum of squared differences] appeared to perform equally good with an average error score of 0.04 (0 is the perfect matching). LSAD was selected for generating the disparity maps

Subjective quality and depth assessment in stereoscopic viewing of volume-rendered medical images

No study to-date explored the relationship between perceived image quality (IQ) and perceived depth (DP) in stereoscopic medical images. However, this is crucial to design objective quality metrics suitable for stereoscopic medical images. This study examined this relationship using volume-rendered stereoscopic medical images for both dual-and single-view distortions. The reference image was modified to simulate common alterations occurring during the image acquisition stage or at the display side: added white Gaussian noise, Gaussian filtering, changes in luminance, brightness and contrast. We followed a double stimulus five-point quality scale methodology to conduct subjective tests with eight non-expert human observers. The results suggested that DP was very robust to luminance, contrast and brightness alterations and insensitive to noise distortions until standard deviation sigma=20 and crosstalk rates of 7%. In contrast, IQ seemed sensitive to all distortions. Finally, for both DP and IQ, the Friedman test indicated that the quality scores for dual-view distortions were significantly worse than scores for single-view distortions for multiple blur levels and crosstalk impairments. No differences were found for most levels of brightness, contrast and noise distortions. So, DP and IQ didn't react equivalently to identical impairments, and both depended whether dual-or single-view distortions were applied

CAMRAD: Development of a Multi-Megagray Radiation Hard CMOS Camera for Dismantling Operations

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