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Updated: Aug 24, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
Published on: November 30, 2022
Comments on: A methodology for evaluation of boundary detection algorithms on medical images
Abstract:
In this paper we analyze a result previously published about a comparison between two statistical tests used for evaluation of boundary detection algorithms on medical images. We conclude that the statement made by Chalana and Kim (1997) about the performance of the percentage test has a weak theoretical foundation, and according to our results, is not correct. In addition, we propose a one-sided hypothesis test for which the acceptance region can be determined in advance, as opposed to the two-sided confidence intervals proposed in the original paper, which change according to the estimated quantity.
