An approach to real-time scan conversion*

Author(s):  
FRANKLIN C. CROW
Keyword(s):  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Nicolás Rosillo ◽  
Javier Del-Águila-Mejía ◽  
Ayelén Rojas-Benedicto ◽  
María Guerrero-Vadillo ◽  
Marina Peñuelas ◽  
...  

Abstract Background On June 21st de-escalation measures and state-of-alarm ended in Spain after the COVID-19 first wave. New surveillance and control strategy was set up to detect emerging outbreaks. Aim To detect and describe the evolution of COVID-19 clusters and cases during the 2020 summer in Spain. Methods A near-real time surveillance system to detect active clusters of COVID-19 was developed based on Kulldorf’s prospective space-time scan statistic (STSS) to detect daily emerging active clusters. Results Analyses were performed daily during the summer 2020 (June 21st – August 31st) in Spain, showing an increase of active clusters and municipalities affected. Spread happened in the study period from a few, low-cases, regional-located clusters in June to a nationwide distribution of bigger clusters encompassing a higher average number of municipalities and total cases by end-August. Conclusion STSS-based surveillance of COVID-19 can be of utility in a low-incidence scenario to help tackle emerging outbreaks that could potentially drive a widespread transmission. If that happens, spatial trends and disease distribution can be followed with this method. Finally, cluster aggregation in space and time, as observed in our results, could suggest the occurrence of community transmission.


1986 ◽  
Vol 5 (2) ◽  
pp. 96-105 ◽  
Author(s):  
Min Hwa Lee ◽  
Joo Han Kim ◽  
Song Bai Park

Author(s):  
S. R. Snare ◽  
H. Torp ◽  
F. Orderud ◽  
B. O. Haugen
Keyword(s):  

1985 ◽  
Vol 7 (3) ◽  
pp. 215-224 ◽  
Author(s):  
Seung-Woo Lee ◽  
Song-Bai Park

An improved scan conversion algorithm for ultrasound compound scanning is proposed. In this algorithm, the input data in the spatial domain is sampled by the concentric square raster sampling (CSRS) method, and the display pixel data are filled by one-dimensional linear interpolation. The reconstruction error of the proposed algorithm is much smaller than that of other algorithms, because only one-dimensional, rather than two-dimensional, interpolation is involved. This algorithm greatly simplifies implementation of a real-time digital scan converter (DSC) for spatial compounding of ultrasound images.


2022 ◽  
Author(s):  
Ahmad Alsayed ◽  
Mostafa R. Nabawy ◽  
Akilu Yunusa-Kaltungo ◽  
Mark K. Quinn ◽  
Farshad Arvin
Keyword(s):  

1996 ◽  
Vol 18 (4) ◽  
pp. 241-260 ◽  
Author(s):  
Chris Basoglu ◽  
Yongmin Kim ◽  
Vikram Chalana

We have developed a new ultrasound scan conversion algorithm that can be executed very efficiently on modern microprocessors. Our algorithm is designed to handle the address calculations and input and output (I/O) data loading concurrently with the interpolation. The processing unit's computing power can be dedicated to performing pixel interpolations while the other operations are handled by an independent direct memory access (DMA) controller. By making intelligent use of the I/O transfer capabilities of the DMA controller, the algorithm avoids spending the processing unit's valuable computing cycles in address calculations and nonactive pixel blanking. Furthermore, the new approach speeds up the computation by utilizing the ability of superscalar and very long instruction word (VLIW) processors to perform multiple operations in parallel. Our scan conversion algorithm was implemented on a multimedia and imaging system based on the Texas Instruments TMS320C80 Multimedia Video Processor (MVP). Computing cycles are spent only on predeterminable nonzero output pixels. For example, an execution time of 11.4 ms was achieved when there are 101,829 nonzero output pixels. This algorithm demonstrates a substantial improvement over previous scan conversion algorithms, and its optimized implementation enables modern commercially available programmable processors to support scan conversion at video rates.


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