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Background/Aims: The identification of significant coronary arterial disease (CAD) is important to reduce perioperative ischemic insult and the possibility of repeated open-chest surgery in patients scheduled to undergo valvular surgery. However, there are no published data on the incidence of significant CAD in these patients. Thus, we examined the prevalence of significant CAD in patients scheduled to undergo valvular surgery. Methods: From January 2005 to June 2011, all consecutive adult patients diagnosed with significant valvular disease and scheduled for an elective open valvular operation were retrospectively investigated at

In this paper, the SMV 3D display method using liquid crystal shutter glass(LCSG) and SPB has been proposed. The proposed SMV display can solve the resolution degradation problem of conventional multiview displays that using based time-multiplexing method. Also, observers fatigue due to the mismatch between accommodation and vergence problem of glass-type 3D displays and conventional multiview displays, can be improved using SMV 3D display method.

Deep learning technology is one of the emerging topics in solving problems in all scientific fields. In this paper, we address a hologram reconstruction method using cascaded multitask networks. A cascaded network consists of two U-net networks. The first is used for conversion between hologram plane and image plane and the other is used for extraction of image and depth. To train the network, we simulate an optical holographic microscopy setup. Experimental results show that the proposed approach can restore effectively complex optical fields and depth information.

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