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Afat, Saif,Brockmann, Carolin,Nikoubashman, Omid,Mü,ller, Marguerite,Thierfelder, Kolja M.,Brockmann, Marc A.,Nikolaou, Konstantin,Wiesmann, Martin,Kim, Jong Hyo,Othman, Ahmed E. Radiological Society of North America 2018 Radiology Vol.287 No.2
<P>Conclusion: The results suggest that radiation dose reduction to 40% of original dose levels (tube current-time product, 72 mAs) may be performed in VP CT imaging of patients with aneurysmal subarachnoid hemorrhage without compromising the diagnostic accuracy regarding detection of cerebral perfusion impairment indicating vasospasm. (C)RSNA, 2018</P>
Othman, A. E.,Brockmann, C.,Yang, Z.,Kim, C.,Afat, S.,Pjontek, R.,Nikoubashman, O.,Brockmann, M. A.,Nikolaou, K.,Wiesmann, M. SPRINGER INTERNATIONAL 2016 EUROPEAN RADIOLOGY Vol.26 No.1
<P>To examine the impact of denoising on ultra-low-dose volume perfusion CT (ULD-VPCT) imaging in acute stroke. Simulated ULD-VPCT data sets at 20 % dose rate were generated from perfusion data sets of 20 patients with suspected ischemic stroke acquired at 80 kVp/180 mAs. Four data sets were generated from each ULD-VPCT data set: not-denoised (ND); denoised using spatiotemporal filter (D1); denoised using quanta-stream diffusion technique (D2); combination of both methods (D1 + D2). Signal-to-noise ratio (SNR) was measured in the resulting 100 data sets. Image quality, presence/absence of ischemic lesions, CBV and CBF scores according to a modified ASPECTS score were assessed by two blinded readers. SNR and qualitative scores were highest for D1 + D2 and lowest for ND (all p a parts per thousand currency signaEuro parts per thousand 0.001). In 25 % of the patients, ND maps were not assessable and therefore excluded from further analyses. Compared to original data sets, in D2 and D1 + D2, readers correctly identified all patients with ischemic lesions (sensitivity 1.0, kappa 1.0). Lesion size was most accurately estimated for D1 + D2 with a sensitivity of 1.0 (CBV) and 0.94 (CBF) and an inter-rater agreement of 1.0 and 0.92, respectively. An appropriate combination of denoising techniques applied in ULD-VPCT produces diagnostically sufficient perfusion maps at substantially reduced dose rates as low as 20 % of the normal scan. aEuro cent Perfusion-CT is an accurate tool for the detection of brain ischemias. aEuro cent The high associated radiation doses are a major drawback of brain perfusion CT. aEuro cent Decreasing tube current in perfusion CT increases image noise and deteriorates image quality. aEuro cent Combination of different image-denoising techniques produces sufficient image quality from ultra-low-dose perfusion CT.</P>
Appropriate Smart Factory for SMEs: Concept, Application and Perspective
정우균,Dong-Ryul Kim,Hyunsu Lee,Tae Hun Lee,Insoon Yang,Byeng D. Youn,Daniel Zontar,Matthias Brockmann,Christian Brecher,Sung-Hoon Ahn 한국정밀공학회 2021 International Journal of Precision Engineering and Vol.22 No.1
In the manufacturing industry, the smart factory is considered the final stage of the Fourth Industrial Revolution. Manufacturing companies are pursuing breakthroughs by introducing various advanced technologies to ensure their competitiveness. However, it is difficult for small and medium-sized enterprises (SMEs) to adopt smart-factory technologies, owing to financial and technical burdens. This paper proposes a smart factory that can be applied technically and strategically to the introduction of a smart factory for SMEs. The concept of an ‘appropriate smart factory’ involves applying appropriate measures in terms of cost and scale with consideration of the situations faced by SMEs. The goal is to build a smart factory that has necessary functions (Essential) but can be easily operated (Simple) at a low cost (Affordable) and has compatibility (Interoperable). This paper presents technical application measures such as appropriate smart sensors, appropriate IoT (Internet of Things), and small data processing, along with the definition of an appropriate smart factory. In addition, a case study was examined where the quality inspection equipment for garment manufacturing SMEs was developed by applying the appropriate smart factory concept.