These methods prove indispensable in abdominal CT images.
Further work is needed in heart ultrasound images.
The methods apply in any domain with consistent image conditions characterizing object boundaries, for which automated identification is nontrivial, perhaps due to interfering detail. An important but neglected task has always been to select image qualities to guide a model. Monotonicity is measured using correlation coefficient and using the newly introduced distance from closest increasing function. Domain-dependent choices must be tested. We analyze several Gaussian models fitting image intensity and perpendicular gradient at the object boundary, as well as the traditional sum of gradient magnitudes.