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I describe recent progress in machine learning in medical ultrasound imaging. At a high level, the two technologies appear to be well-matched as the former attempts to make sense of complex patterns, and the latter can generate images of complex acoustic patterns. Thus, the general challenge to the image analysis practitioner is to design machine learning architectures that model the patterns in real...
We present a fully automatic method to segment the skull from 2-D ultrasound images of the fetal head and to compute the standard biometric measurements derived from the segmented images. The method is based on the minimization of a novel cost function. The cost function is formulated assuming that the fetal skull has an approximately elliptical shape in the image and that pixel values within the...
Accurate and robust image analysis software is crucial for assessing the quality of ultrasound images of fetal biometry. In this work, we present the result of our automated image analysis method based on a machine learning algorithm in detecting important anatomical landmarks employed in manual scoring of ultrasound images of the fetal abdomen. Experimental results on 2384 images are promising and...
It is an exciting time for imaging in perinatal care. Technical advances in imaging technology mean that good quality clinical 3D ultrasound images of the growing fetus can be acquired from an early gestational age (GA) (11 weeks GA onwards). With the help of advances in MR-based reconstruction which compensate for fetal motion, high quality images of the fetal brain (and other organs) can be obtained...
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