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BACKGROUND: EarWell infant ear molding device is a noninvasive, nonsurgical option to treat ear deformities in early infancy. There are no studies involving the parents' perspective to the use of the EarWell. AIM: To investigate our experience with EarWell infant ear molding device and to assess the parents' satisfaction. STUDY DESIGN: A retrospective case series study of infants with congenital ear deformities who were treated with EarWell device from October 2021 to November 2022. Demographic and clinical data were collected. Clinical photographs were obtained before, during, and after treatment. Parents' satisfaction level was assessed through telephone encounters and surveys, and issues associated with device application were identified. Clinical improvement of ear deformity was graded into poor, fair, good, and excellent. RESULTS: A total of 9 patients with congenital ear deformities were identified and included in this study (7 bilateral deformities and 2 unilateral deformities). The mean adjusted age of the initial treatment is 17 weeks (4-23 weeks), and the mean treatment duration is 5.7 weeks. The authors received full 8 responses from the parents' survey, and all parents were satisfied with post-treatment results (4 satisfied, 1 fully satisfied, and 2 very satisfied). Issues associated with device application were 3 superficial skin ulcers and 4 skin irritation. Clinical Improvement grades were: 5 excellent improvement, 2 good improvement, and 2 fair improvement. CONCLUSIONS: On the basis of our experience, the EarWell device has shown a high success rate and a low complication rate. It is well accepted by parents, but it needs close follow-up to detect minor device-related issues. The device is safe for multiple skin types.
RESUMO
This paper addresses the problem of calibrating camera lens distortion, which can be significant in medium to wide angle lenses. Our approach is based on the analysis of distorted images of straight lines. We derive new distortion measures that can be optimized using nonlinear search techniques to find the best distortion parameters that straighten these lines. Unlike the other existing approaches, we also provide fast, closed-form solutions to the distortion coefficients. We prove that including both the distortion center and the decentering coefficients in the nonlinear optimization step may lead to instability of the estimation algorithm. Our approach provides a way to get around this, and, at the same time, it reduces the search space of the calibration problem without sacrificing the accuracy and produces more stable and noise-robust results. In addition, while almost all existing nonmetric distortion calibration methods needs user involvement in one form or another, we present a robust approach to distortion calibration based on the least-median-of-squares estimator. Our approach is, thus, able to proceed in a fully automatic manner while being less sensitive to erroneous input data such as image curves that are mistakenly considered projections of three-dimensional linear segments. Experiments to evaluate the performance of this approach on synthetic and real data are reported.
