Arvinti Beatrice, Iacob Emil Radu, Isar Alexandru, Iacob Daniela, Costache Marius
Fundamentals of Physics for Engineers Department, "Politehnica" University Timisoara, Bd. Vasile Pârvan 2, 300223 Timisoara, Romania.
Department of Pediatric Surgery, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania.
J Pers Med. 2022 Aug 18;12(8):1328. doi: 10.3390/jpm12081328.
(1) Background: The prevention of critical situations is a key ability in medicine. Hip ultrasound for neonates is a standard procedure to prevent later critical outcomes, such as hip dysplasia. Additionally, the SARS-CoV-2 pandemic has put worldwide stress upon healthcare units, resulting often in a lack of sufficient medical personnel. This work aims to develop solutions to ease and speed up the process of coming to a correct diagnosis. (2) Methods: Traditional medical procedures are envisaged, but they are enhanced to reduce diagnosing errors due to the movements of the neonates. Echographic noise filtering and contrast correction methods are implemented the Hyperanalytic Wavelet Transform, combined with an adaptive Soft Thresholding Filter. The algorithm is tailored to infants' structure and is tested on real ultrasounds provided by the "Victor Babes" University of Medicine and Pharmacy. Denoising and contrast correction problems are targeted. (3) Results: In available clinical cases, the noise affecting the image was reduced and the contrast was enhanced. (4) Discussion: We noticed that a significant amount of noise can be added to the image, as the patients are neonates and can hardly avoid movements. (5) Conclusions: The algorithm is personalized with no fixed reference value. Any device easing the clinical procedures of physicians has a practical medical application.
(1) 背景：预防危急情况是医学中的一项关键能力。新生儿髋关节超声检查是预防诸如髋关节发育不良等后期危急后果的标准程序。此外，新冠疫情给全球医疗机构带来了压力，常常导致医疗人员不足。这项工作旨在开发解决方案，以简化并加快做出正确诊断的过程。(2) 方法：设想了传统医疗程序，但对其进行了改进，以减少因新生儿活动导致的诊断错误。采用超解析小波变换结合自适应软阈值滤波器实现了超声噪声滤波和对比度校正方法。该算法针对婴儿的结构进行了定制，并在“维克托·巴比什”医科药科大学提供的真实超声图像上进行了测试。针对去噪和对比度校正问题展开研究。(3) 结果：在现有的临床病例中，影响图像的噪声减少，对比度增强。(4) 讨论：我们注意到，由于患者是新生儿，几乎无法避免活动，图像可能会添加大量噪声。(5) 结论：该算法是个性化的，没有固定参考值。任何简化医生临床程序的设备都具有实际医疗应用价值。
