Abstract: Examples for determining a confidence level associated with image segmentation are disclosed. A confidence level associated with a collective image segmentation result can be determined by generating multiple individual segmentation results each from the same image data. These examples can then aggregate the individual segmentation results to form the collective image segmentation result and measure the spread of each individual segmentation result from the collective image segmentation result. The measured spread of each individual segmentation result can then be used to determine the confidence level associated with the collective image segmentation result. This can allow a confidence level associated with the collective image segmentation result to be determined. This confidence level may be determined without needing a ground truth to compare to the collective image segmentation result.

Abstract: Examples for determining a confidence level associated with image segmentation are disclosed. A confidence level associated with a collective image segmentation result can be determined by generating multiple individual segmentation results each from the same image data. These examples can then aggregate the individual segmentation results to form the collective image segmentation result and measure the spread of each individual segmentation result from the collective image segmentation result. The measured spread of each individual segmentation result can then be used to determine the confidence level associated with the collective image segmentation result. This can allow a confidence level associated with the collective image segmentation result to be determined. This confidence level may be determined without needing a ground truth to compare to the collective image segmentation result.

Abstract: Examples for determining a confidence level associated with image segmentation are disclosed. A confidence level associated with a collective image segmentation result can be determined by generating multiple individual segmentation results each from the same image data. These examples can then aggregate the individual segmentation results to form the collective image segmentation result and measure the spread of each individual segmentation result from the collective image segmentation result. The measured spread of each individual segmentation result can then be used to determine the confidence level associated with the collective image segmentation result. This can allow a confidence level associated with the collective image segmentation result to be determined. This confidence level may be determined without needing a ground truth to compare to the collective image segmentation result.

Abstract: Examples for determining a confidence level associated with image segmentation are disclosed. A confidence level associated with a collective image segmentation result can be determined by generating multiple individual segmentation results each from the same image data. These examples can then aggregate the individual segmentation results to form the collective image segmentation result and measure the spread of each individual segmentation result from the collective image segmentation result. The measured spread of each individual segmentation result can then be used to determine the confidence level associated with the collective image segmentation result. This can allow a confidence level associated with the collective image segmentation result to be determined. This confidence level may be determined without needing a ground truth to compare to the collective image segmentation result.

Abstract: One method for assessing a vessel can include obtaining a set of first location pressure measurements at a first location in the vessel over a first time period and a set of second location pressure measurements at a second location in the vessel over the first time period. This method can further include identifying a first leading characteristic associated with one or more pressure measurements in the set of first location pressure measurements, a second leading characteristic associated with one or more pressure measurements in the set of second location pressure measurements, a first trailing characteristic associated with one or more pressure measurements in the set of first location pressure measurements, and a second trailing characteristic associated with one or more pressure measurements in the set of second location pressure measurements. And, this method can include calculating a pressure ratio using pressure measurements between the identified characteristics.

Abstract: One method for assessing a vessel can include obtaining a set of first location pressure measurements at a first location in the vessel over a first time period and a set of second location pressure measurements at a second location in the vessel over the first time period. This method can further include identifying a first leading characteristic associated with one or more pressure measurements in the set of first location pressure measurements, a second leading characteristic associated with one or more pressure measurements in the set of second location pressure measurements, a first trailing characteristic associated with one or more pressure measurements in the set of first location pressure measurements, and a second trailing characteristic associated with one or more pressure measurements in the set of second location pressure measurements. And, this method can include calculating a pressure ratio using pressure measurements between the identified characteristics.

Abstract: One method for assessing a vessel can include obtaining a set of first location pressure measurements at a first location in the vessel over a first time period and a set of second location pressure measurements at a second location in the vessel over the first time period. This method can further include identifying a first leading characteristic associated with one or more pressure measurements in the set of first location pressure measurements, a second leading characteristic associated with one or more pressure measurements in the set of second location pressure measurements, a first trailing characteristic associated with one or more pressure measurements in the set of first location pressure measurements, and a second trailing characteristic associated with one or more pressure measurements in the set of second location pressure measurements. And, this method can include calculating a pressure ratio using pressure measurements between the identified characteristics.

Abstract: A Legionella specific antibiotic AL072 is disclosed. In addition the antibiotic is produced by the microorganism Streptomyces sp. AL91KCCM 10055. Further, the antibiotic compound has a specified formula.