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A Rapid Segmentation-Insensitive “Digital Biopsy” Method for Radiomic Feature Extraction: Method and Pilot Study Using CT Images of Non–Small Cell Lung Cancer

机译：用于辐射特征提取的快速分割 - 不敏感“数字活检”方法：使用非小细胞肺癌CT图像的方法和试验研究

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Sebastian Echegaray; Viswam Nair; Michael Kadoch; Ann Leung; Daniel Rubin; Olivier Gevaert; Sandy Napel;
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年度 2016
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1. Machine learning to predict lung nodule biopsy method using CT image features: A pilot study [J] . Sumathipala Yohan, Shafiq Majid, Bongen Erika, Computerized Medical Imaging and Graphics: The Official Jounal of the Computerized Medical Imaging Society . 2019,第期

机译：机器学习预测使用CT图像特征的肺结核活检方法：试验研究
2. Impact of feature selection methods and subgroup factors on prognostic analysis with CT-based radiomics in non-small cell lung cancer patients [J] . Yuto Sugai, Noriyuki Kadoya, Shohei Tanaka, Radiation oncology . 2021,第1期

机译：特征选择方法与亚群因子对非小细胞肺癌患者CT基覆射瘤预后分析的影响
3. Radiomics study for predicting the expression of PD-L1 in non -small cell lung cancer based on CT images and clinicopathologic features [J] . Journal of X-ray science and technology . 2020,第3期

机译：基于CT图像和临床病理特征的基于CT图像和临床病理特征来预测非-Small细胞肺癌中PD-L1的表达的辐射瘤研究
4. Effects of small and rapid temperature oscillations on adherent cell cultures: Exposure system, experimental method and a pilot study on human cancer cells [C] . L.A. Portelli, A. Kausik, F.S. Barnes European Medical Biological Engineering Conference . 2018

机译：小快速振荡对粘附细胞培养物的影响：暴露系统，实验方法和人癌细胞的试验研究
5. Radiomic Feature Variability on Cone-Beam CT Images for Lung SBRT [D] . Geng, Ruiqi. 2018

机译：肺SBRT的锥形束CT图像的放射特征变化
6. A Rapid Segmentation-Insensitive Digital Biopsy Method for Radiomic Feature Extraction: Method and Pilot Study Using CT Images of Non–Small Cell Lung Cancer [O] . Sebastian Echegaray, Viswam Nair, Michael Kadoch, 2016

机译：快速分割不敏感的数字活检方法进行放射学特征提取：使用非小细胞肺癌CT图像的方法和试点研究
7. ABSTRACT Various body parts or organs can be analysed to identify the different diseases in the human body. Fingernail analysis is one of the ways to identify disease in the human body. Nails are the body part which are farthest from the heart and therefore receive oxygen at last. As a result the nails are the first who show the symptoms of a disease in the human body. Fingernails can be easily captured for diagnosis and there are no heavy equipment or no specific conditions required to use nail image for disease diagnosis, like in other tests and scanning processes. Human nails deliver beneficial information about complaints or any nutritive imbalances in the human body depending upon their shape, texture and colour. In human beings, numerous systemic and skin diseases can be easily analyzed through careful examination of nails of both the limbs. A lot of nail illnesses have been found to be primary signs of numerous underlying systemic illnesses. The colour, texture or shape changes in nails are signs of many diseases mainly affecting nails. Considering all these properties of nails a system is proposed that uses digital image processing (DIP) methods for identifying such changes in the human nail to get more precise results and predict numerous diseases effortlessly. With the emerging Internet of Things (IOT) concept the generated report is made available remotely, this will help users to reduce transportation efforts. As the system has to deal with large and private data, the security of data must be ensured. To keep the data confidential, the Blockchain concept which is one of the most emerging concepts in the field of data management is used. The paper contains the implementation of the digital image processing for feature extraction of nail images, usage of IOT (ThingSpeak cloud) for data storage and implementation of Blockchain to keep the system secured and theft free. KEY WORDS: Int ernet of thin gs (IOT), Image proc essin g, Thin gSpeak, RG B vavalues, Mean pi xel vavalues, Bloc kchain , Hash key. Disease Diagnostic System: Abnormalities in Human Nail [O] . Pranav S. Wazarkar 2020

机译：摘要的各个身体部位或器官可被分析以识别在人体内的不同的疾病。指甲分析来识别人体疾病的方法之一。指甲是身体一部分是离心脏最远，因此在最后接受氧气。作为结果，指甲是第一谁表现出人体疾病的症状。指甲可以容易地捕获用于诊断和没有重装或需要使用指甲图像用于疾病诊断，比如在其他测试和扫描过程没有特定的条件。人的指甲提供有关投诉或取决于它们的形状，纹理和色彩在人体内的任何营养失衡有益的信息。在人类中，许多全身性皮肤疾病是可以很容易地通过两个四肢指甲的仔细检查分析。很多指甲病已发现众多潜在系统性疾病的主要症状。在指甲的颜色，质地和形状的变化是许多疾病主要影响指甲的迹象。考虑到所有的指甲的这些性能的系统被提出，用于识别人指甲这样的变化以获得更精确的结果，并毫不费力预测许多疾病用途的数字图像处理（DIP）方法。随着物联网（IOT）的概念，新兴的互联网将生成的报告提供远程，这将帮助用户降低运输工作。由于系统必须处理大量的私人数据，数据的安全性必须得到保证。为了保持数据的机密性，使用Blockchain的概念，它是在数据管理领域的大多数新兴的概念之一。本文包含了数字图像处理的指甲图像，IOT（ThingSpeak云）的使用为数据存储和执行Blockchain的特征提取的执行，以保持固定的系统和盗窃免费。关键词：诠释薄GS（IOT），图像的ERNET PROC essin克，薄型gSpeak，RG乙vavalues，平均数PI XEL vavalues，阵营kchain，哈希密钥。疾病诊断系统：在人类指甲异常

A Rapid Segmentation-Insensitive “Digital Biopsy” Method for Radiomic Feature Extraction: Method and Pilot Study Using CT Images of Non–Small Cell Lung Cancer

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