An automatic method for measuring the fetal mean abdominal diameter (MAD) or abdominal circumference (AC) with ultrasound is proposed. From a correctly presented abdominal section suitable for MAD or AC measurement, t...An automatic method for measuring the fetal mean abdominal diameter (MAD) or abdominal circumference (AC) with ultrasound is proposed. From a correctly presented abdominal section suitable for MAD or AC measurement, the location of fetal abdomen is detected by image processing. Thereafter, an active contour model is converged along the abdominal boundary for measurement purposes. The validation data set contained 310 images of fetuses with gestational age (GA) from 14 to 41 weeks. The measurement success rate was 88.1%. By manually indicating the location of the abdomen, the success rate was further improved to 95.8% for the failed cases. The correlation between manual and automatic measurements was 0.95 and the intraclass correlation coefficient (ICC) was 0.976 (95% confidence interval (CI);0.969 - 0.981). The average method execution time was 0.3 s. The mean error was lower in young fetuses (0.4%) than in older fetuses (-2.1%). The proposed cross-platform method was implemented on a portable, low-cost ultrasound machine prototype targeted for low- and middle-income countries (LMIC);the results achieved were comparable to those of other state-of-the-art automatic methods.展开更多
An automatic method able to recognize a presented section through the biparietal plane of the fetal head and a section through the fetal femur in ultrasound images is developed. Once the correct anatomical section for...An automatic method able to recognize a presented section through the biparietal plane of the fetal head and a section through the fetal femur in ultrasound images is developed. Once the correct anatomical section for measurement is identified by the machine, the placement of the measurement calipers is automatically determined by fitting an active contour model to the structure of interest. The fetal biparietal diameter (BPD) and femur length (FL) are then measured automatically. The validation data set contained 167 and 197 B-mode images for BPD and FL measurements, respectively. The images were acquired using 4 different ultrasound scanners, which resulted in varied image quality and gain settings. The mean gestational age (GA) of the fetuses was 19.4 weeks, range 16 to 41 weeks. A measurement success rate of 90% was achieved for both BPD and FL. The correlation coefficients between the manual and automatic measurements were 0.995 (BPD) and 0.967 (FL), mean errors were 0.5 mm (BPD) and -1.7 mm (FL) and error range with 95% confidence interval (CI) were ﹣3.8 - 4.8 mm (BPD) and ﹣11.4 - 8.1 mm (FL). The automatic measurement results were consistent in both high and low gain settings. The intraclass correlation coefficients between manual and automatic measurements were 0.995 (95% CI;0.981 - 0.999) for BPD in high gain, 1.0 (95% CI;0.998 - 1.0) for BPD in low gain, 0.998 (95% CI;0.991 - 0.999) for FL in high gain and 0.999 (95% CI;0.996 - 1.0) for FL in low gain settings. The method was implemented on a prototype, portable ultrasound machine designed to be used in low- and middle-income countries (LMIC). The overall performance of the method supports our hypothesis that automated methods can be used and are beneficial in a clinical setting.展开更多
文摘An automatic method for measuring the fetal mean abdominal diameter (MAD) or abdominal circumference (AC) with ultrasound is proposed. From a correctly presented abdominal section suitable for MAD or AC measurement, the location of fetal abdomen is detected by image processing. Thereafter, an active contour model is converged along the abdominal boundary for measurement purposes. The validation data set contained 310 images of fetuses with gestational age (GA) from 14 to 41 weeks. The measurement success rate was 88.1%. By manually indicating the location of the abdomen, the success rate was further improved to 95.8% for the failed cases. The correlation between manual and automatic measurements was 0.95 and the intraclass correlation coefficient (ICC) was 0.976 (95% confidence interval (CI);0.969 - 0.981). The average method execution time was 0.3 s. The mean error was lower in young fetuses (0.4%) than in older fetuses (-2.1%). The proposed cross-platform method was implemented on a portable, low-cost ultrasound machine prototype targeted for low- and middle-income countries (LMIC);the results achieved were comparable to those of other state-of-the-art automatic methods.
文摘An automatic method able to recognize a presented section through the biparietal plane of the fetal head and a section through the fetal femur in ultrasound images is developed. Once the correct anatomical section for measurement is identified by the machine, the placement of the measurement calipers is automatically determined by fitting an active contour model to the structure of interest. The fetal biparietal diameter (BPD) and femur length (FL) are then measured automatically. The validation data set contained 167 and 197 B-mode images for BPD and FL measurements, respectively. The images were acquired using 4 different ultrasound scanners, which resulted in varied image quality and gain settings. The mean gestational age (GA) of the fetuses was 19.4 weeks, range 16 to 41 weeks. A measurement success rate of 90% was achieved for both BPD and FL. The correlation coefficients between the manual and automatic measurements were 0.995 (BPD) and 0.967 (FL), mean errors were 0.5 mm (BPD) and -1.7 mm (FL) and error range with 95% confidence interval (CI) were ﹣3.8 - 4.8 mm (BPD) and ﹣11.4 - 8.1 mm (FL). The automatic measurement results were consistent in both high and low gain settings. The intraclass correlation coefficients between manual and automatic measurements were 0.995 (95% CI;0.981 - 0.999) for BPD in high gain, 1.0 (95% CI;0.998 - 1.0) for BPD in low gain, 0.998 (95% CI;0.991 - 0.999) for FL in high gain and 0.999 (95% CI;0.996 - 1.0) for FL in low gain settings. The method was implemented on a prototype, portable ultrasound machine designed to be used in low- and middle-income countries (LMIC). The overall performance of the method supports our hypothesis that automated methods can be used and are beneficial in a clinical setting.
