A. A. Ruhaima, Dunya Mohee Hayder, Jamal Kamil Al-Rudaini
{"title":"医学图像恢复的人类视觉系统算法","authors":"A. A. Ruhaima, Dunya Mohee Hayder, Jamal Kamil Al-Rudaini","doi":"10.1109/AGERS56232.2022.10093530","DOIUrl":null,"url":null,"abstract":"The human body is such a complicated structure full of fine details, small and big details, some diseases affect the small parts of the body, so a doctor has to use every tool to diagnose the disease like Lab testing and imaging (Imaging means sending the patient to do X-Ray, MRI, CT scan, etc.). So, receiving a clear image with no noise is important to reach a precise diagnosis rather than a different one. Thus, finding a program to find the lost data due to noise is the dream of every physician. A nonlinear two-dimensional image restoration filter structure is introduced in this work. A nonlinear prediction structure is proposed using nonlinear elements depending on the eye's visual phenomena of noise detection. Filter stability is demanded in this structure. Impulse noise recovery is guaranteed in this filter. An advantage of the filter is in preserving textures and keeping fine details. Median-based filters are proposed for noise recovery. The filter structure shows a superior method for noise detection and precise location determination.","PeriodicalId":370213,"journal":{"name":"2022 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Human Visual System Algorithm for Medical Images Recovery\",\"authors\":\"A. A. Ruhaima, Dunya Mohee Hayder, Jamal Kamil Al-Rudaini\",\"doi\":\"10.1109/AGERS56232.2022.10093530\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The human body is such a complicated structure full of fine details, small and big details, some diseases affect the small parts of the body, so a doctor has to use every tool to diagnose the disease like Lab testing and imaging (Imaging means sending the patient to do X-Ray, MRI, CT scan, etc.). So, receiving a clear image with no noise is important to reach a precise diagnosis rather than a different one. Thus, finding a program to find the lost data due to noise is the dream of every physician. A nonlinear two-dimensional image restoration filter structure is introduced in this work. A nonlinear prediction structure is proposed using nonlinear elements depending on the eye's visual phenomena of noise detection. Filter stability is demanded in this structure. Impulse noise recovery is guaranteed in this filter. An advantage of the filter is in preserving textures and keeping fine details. Median-based filters are proposed for noise recovery. The filter structure shows a superior method for noise detection and precise location determination.\",\"PeriodicalId\":370213,\"journal\":{\"name\":\"2022 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AGERS56232.2022.10093530\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AGERS56232.2022.10093530","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Human Visual System Algorithm for Medical Images Recovery
The human body is such a complicated structure full of fine details, small and big details, some diseases affect the small parts of the body, so a doctor has to use every tool to diagnose the disease like Lab testing and imaging (Imaging means sending the patient to do X-Ray, MRI, CT scan, etc.). So, receiving a clear image with no noise is important to reach a precise diagnosis rather than a different one. Thus, finding a program to find the lost data due to noise is the dream of every physician. A nonlinear two-dimensional image restoration filter structure is introduced in this work. A nonlinear prediction structure is proposed using nonlinear elements depending on the eye's visual phenomena of noise detection. Filter stability is demanded in this structure. Impulse noise recovery is guaranteed in this filter. An advantage of the filter is in preserving textures and keeping fine details. Median-based filters are proposed for noise recovery. The filter structure shows a superior method for noise detection and precise location determination.