## 6 Conclusions  
The adaptive SNR threshold method (AdSTM), developed in a previous preliminary study, was tested on a sample of medical US scanners in two different configuration settings. In particular, data was acquired on the same tissue-mimicking phantom from four US diagnostic systems, each equipped with three different US probes that worked at their own central frequency. The AdSTM outcomes were compared with the results from: (a) another automatic method taken from the current state of the art (tangent threshold method, TTM) developed by the same authors and, (b) the mean judgment of eight different observers without medical expertise. Each observer independently performed the test through an in-house MATLAB software preserving the same acquisition conditions. Both AdSTM and TTM repeatability uncertainties were estimated through MCS and subsequently combined with the probe placement uncertainty.  
The outcomes usually showed measurement compatibility among both the automatic methods and the observers' judgment. However, it should be noted that the naked eye test scores' compatibility was conditioned by the large observer sample and by the high number of test repetitions. In QA programs where DOP assessment is still visually carried on by a single operator, such compatibility could be no longer guaranteed, whereas, the application of the AdSTM and the TTM assure reproducibility and traceability because of the algorithm threshold that does not depend on the subjectivity of the technician. Nevertheless, the AdSTM seems to have a higher sensitivity than the TTM because of higher DOP values. Both methods have the advantage of the simplicity in electronic noise estimation because, in the first case it can be directly retrieved from the in-air clip, while in the second, such problems are bypassed through the GSMF evaluation. Nevertheless, in correspondence of a US scanner with limited gray level dynamic range, the TTM seemed to be less reliable. Moreover, the AdSTM required lower computing performance and lower acquisition as well as processing time, excluding the (same) probe positioning and data transfer procedure. With regard to the acquisition time, the TTM needed the acquisition of at least 60 images by varying the STC configuration and the overall gain for the GSMF evaluation, whereas in the AdSTM the acquisition of only two clips of 2 s each one with a US scanner frame rate in the range of 20-30 Hz was required. As a final remark, it should be pointed out that the AdSTM application usually took half the time of the TTM. On the basis of the above results and their limitations, further developments of the present study could be the application of the AdSTM to DOP measurements on (a) a wide number of US diagnostic systems available in the market and (b) different US phantom models, as well as (c) changing US system settings. Such follow-up studies will allow for the selection of the best US system settings for DOP measurement and the improvement of AdSTM robustness and will contribute to providing a reference measurement standard in ultrasound DOP measurements.  
Conceptualization, G.F. and A.S.; methodology, G.F. and F.F.; software, G.F.; validation, G.F., F.F., and A.S.; formal analysis, G.F.; investigation, G.F., F.F., and A.S.; resources, J.G. and S.A.S.; data curation, G.F.; writing--original draft preparation, G.F. and F.F.; writing--review and editing, G.F., F.F., A.S., J.G., S.C., and S.A.S.; visualization, G.F.; supervision, A.S., S.C., and S.A.S.; project administration, A.S.; funding acquisition, J.G. and S.A.S. All authors have read and agreed to the published version of the manuscript. This research received no external funding.  
The authors wish to thank SAMSUNG Healthcare, PHILIPS Healthcare, SIEMENS Healthineers, and ESAOTE for hardware supply and technical assistance in data collection.  
The authors declare no conflict of interest.