## 3 Results and Discussion
### MR Imaging Techniques: General or Special Method  
Papers on related MR image acquisition techniques were classified into three types for systematic review: general, special, and including \"both\" techniques. For papers on general techniques, the results of the application of the NLM noise reduction algorithm to T1 weighted, T2 weighted, and PD weighted images were classified. For papers on special techniques, the results from the use of other techniques, not classified as general techniques, were summarized. Figure 4 presents the overall publication numbers for each type of MR imaging technique using the NLM noise reduction algorithm. Table 2 describes the characteristics for MR imaging techniques of the 25 included studies.  
Of the 25 papers identified, the general technique category had the largest number of papers (_n_ = 13) [39, 43, 45, 46, 48, 50, 53, 54, 55, 56, 58, 62, 63], followed by the special technique category (_n_ = 7) [40, 41, 42, 52, 59, 60, 61], and then the category of \"both\" techniques (_n_ = 5) [44, 47, 49, 51, 57]. Papers related to the application of the NLM noise reduction algorithm in conjunction with general MR imaging acquisition techniques were first published in 2008.  
Among papers on the general techniques, the results from simultaneously studying the T1, T2, and PD weighted images were the most frequent (_n_ = 7), followed by the results from the application of only the T1 weighted image (_n_ = 4), and finally the results from simultaneously studying the T1 and T2 weighted images (_n_ = 2). Additionally, of the special techniques, results from studying DWI (_n_ = 2) or dynamic contrast enhance (_n_ = 2) were the most frequent, and various application fields were derived from \"both.\" The results from the majority of the studies included in the \"both\" category applied the algorithm to both the \"general techniques\" and \"DWI or DTI\". The basic weighted image techniques generally showed a tendency to preferentially analyze the effects of the image processing algorithm. Numerous results have been reached from the analysis of diffusion images, in which noise characteristics are very important.  
Figure 4: (**a**) Graph of the number of publications for the various MR image acquisition techniques using the NLM noise reduction algorithm. The final classification included 25 papers; of those, three major categories of techniques were investigated. (**b**) The total number of papers as a function of the publication year.  
The development of MR imaging technology, including DWI using an echo planar imaging (EPI) pulse sequence, has changed the paradigm of diagnosis and treatment of cerebral infarctions. DWI is a method of imaging the degree of diffusion of water molecules in the human body using MR imaging. In the case of acute cerebral infarctions, the MR imaging shows a decrease in the apparent diffusion coefficient and shows a higher signal intensity than for normal brain parenchyma. DWI has been verified as an excellent technique to detect the infarction region in the brain, and it was found that the majority of research is focused on increasing the efficiency of infarction diagnosis by removing noise [47; 49; 51; 60; 61].  
After analyzing the number of publications by year, it was determined that all three techniques showed a tendency to remain largely unchanged.