Pub Date : 2022-02-03DOI: 10.5772/intechopen.101808
Reda R. Gharieb
This chapter gives a review for both conventional X-ray and computed tomography (CT) scan imaging modalities and their medical applications. The chapter presents a brief history on the discovery of X-ray, X-ray imaging, and computed tomography scan. The linear projection for the generation of the sinogram (the detector’s signals versus the rotational angle) and the filtered backprojection for image reconstruction are discussed. Computer simulations for linear and fan beams X -ray are also presented. The chapter discusses some medical applications of both the conventional X-ray and CT scan imaging.
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Pub Date : 2022-01-31DOI: 10.5772/intechopen.102573
Anil K. Bharodiya
Medical image processing covers various types of images such as tomography, mammography, radiography (X-Ray images), cardiogram, CT scan images etc. Once the CT scan image is captured, Doctors diagnose it to detect abnormal or normal condition of the captured of the patient’s body. In the computerized image processing diagnosis, CT-scan image goes through sophisticated phases viz., acquisition, image enhancement, extraction of important features, Region of Interest (ROI) identification, result interpretation etc. Out of these phases, a feature extraction phase plays a vital role during automated/computerized image processing to detect ROI from CT-scan image. This phase performs scientific, mathematical and statistical operations/algorithms to identify features/characteristics from the CT-scan image to shrink image portion for diagnosis. In this chapter, I have presented an extensive review on “Feature Extraction” step of digital image processing based on CT-scan image of human being.
{"title":"Feature Extraction Methods for CT-Scan Images Using Image Processing","authors":"Anil K. Bharodiya","doi":"10.5772/intechopen.102573","DOIUrl":"https://doi.org/10.5772/intechopen.102573","url":null,"abstract":"Medical image processing covers various types of images such as tomography, mammography, radiography (X-Ray images), cardiogram, CT scan images etc. Once the CT scan image is captured, Doctors diagnose it to detect abnormal or normal condition of the captured of the patient’s body. In the computerized image processing diagnosis, CT-scan image goes through sophisticated phases viz., acquisition, image enhancement, extraction of important features, Region of Interest (ROI) identification, result interpretation etc. Out of these phases, a feature extraction phase plays a vital role during automated/computerized image processing to detect ROI from CT-scan image. This phase performs scientific, mathematical and statistical operations/algorithms to identify features/characteristics from the CT-scan image to shrink image portion for diagnosis. In this chapter, I have presented an extensive review on “Feature Extraction” step of digital image processing based on CT-scan image of human being.","PeriodicalId":325825,"journal":{"name":"Computed Tomography Scan [Working Title]","volume":"385 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124781443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-04DOI: 10.5772/intechopen.101197
I. Niang, G. Akpo, Khadidiatou Ndiaye Diouf, S. Ba
CT is a medical imaging technique that uses X-rays to provide three-dimensional reconstructed images of the explored anatomical region. Its sensitivity has already been demonstrated in the exploration of pulmonary lesions of traumatic, neoplastic and especially infectious origin. In this chapter we present and highlight the usefulness of CT-scan imaging for diagnosis and management of the thoracic involvement of the COVID-19 pandemic. We also present the use of CT in extra-thoracic involvement, in particular, the angio-CT of the limbs in cases of suspected arterial thrombosis of the limbs during COVID-19. Finally, we evoke the other tools such as artificial intelligence which coupled with the CT-scan allows a greater accuracy and thus are to popularize in order to reinforce the CT as a tool of first plan in the fight against future pandemics with thoracic tropism.
{"title":"Use of Computed Tomography (CT)-Scan in the Current Coronavirus Pandemic","authors":"I. Niang, G. Akpo, Khadidiatou Ndiaye Diouf, S. Ba","doi":"10.5772/intechopen.101197","DOIUrl":"https://doi.org/10.5772/intechopen.101197","url":null,"abstract":"CT is a medical imaging technique that uses X-rays to provide three-dimensional reconstructed images of the explored anatomical region. Its sensitivity has already been demonstrated in the exploration of pulmonary lesions of traumatic, neoplastic and especially infectious origin. In this chapter we present and highlight the usefulness of CT-scan imaging for diagnosis and management of the thoracic involvement of the COVID-19 pandemic. We also present the use of CT in extra-thoracic involvement, in particular, the angio-CT of the limbs in cases of suspected arterial thrombosis of the limbs during COVID-19. Finally, we evoke the other tools such as artificial intelligence which coupled with the CT-scan allows a greater accuracy and thus are to popularize in order to reinforce the CT as a tool of first plan in the fight against future pandemics with thoracic tropism.","PeriodicalId":325825,"journal":{"name":"Computed Tomography Scan [Working Title]","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127946031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-04DOI: 10.5772/intechopen.100177
Elena Ivanovna Matkevich, Ivan Vasilievich Ivanov
Accounting for the effective dose (ED, mSv) and calculating the radiation risk during CT is necessary to predict the long-term consequences of radiation exposure on the population. We analyzed the results of 1003 CT examinations of the chest in patients with suspected COVID-19 in the city diagnostic center. The average ED and confidence intervals (p ≤ 0.05) for patients with a single CT scan were: children (12–14 years) 2.59 ± 0.19 mSv, adolescents (15–19 years) 3.23 ± 0.17 mSv, adults (20–64 years), 3.43 ± 0.08 mSv, older persons (65 years and older) 3.28 ± 0.19 mSv. The maximum radiation risk values were 31.2*10–5 in women children and 29.3*10–5 in women adolescents, which exceeds the risk values for men in these age groups by 2.3 and 1.9 times, respectively. For the group of adult patients the risk was 11.2*10–5 in men and 17.4*10–5 in women, which is 1.6 times higher than in men. All these risk values are in the range of 10*10–5–100*10–5, which corresponds to the level LOW. For the group of older age patients, the radiation risk was 2.6*10–5, which corresponds to the level of 1*10–5–10*10–5, VERY LOW. Our materials shows in detail the technique to evaluate effective radiation doses for chest CT and calculate the radiation risk of the carcinogenic effects of this exposure.
{"title":"Radiation Doses and Risk Assessment during Computed Tomography of the Chest in COVID-19 Patients","authors":"Elena Ivanovna Matkevich, Ivan Vasilievich Ivanov","doi":"10.5772/intechopen.100177","DOIUrl":"https://doi.org/10.5772/intechopen.100177","url":null,"abstract":"Accounting for the effective dose (ED, mSv) and calculating the radiation risk during CT is necessary to predict the long-term consequences of radiation exposure on the population. We analyzed the results of 1003 CT examinations of the chest in patients with suspected COVID-19 in the city diagnostic center. The average ED and confidence intervals (p ≤ 0.05) for patients with a single CT scan were: children (12–14 years) 2.59 ± 0.19 mSv, adolescents (15–19 years) 3.23 ± 0.17 mSv, adults (20–64 years), 3.43 ± 0.08 mSv, older persons (65 years and older) 3.28 ± 0.19 mSv. The maximum radiation risk values were 31.2*10–5 in women children and 29.3*10–5 in women adolescents, which exceeds the risk values for men in these age groups by 2.3 and 1.9 times, respectively. For the group of adult patients the risk was 11.2*10–5 in men and 17.4*10–5 in women, which is 1.6 times higher than in men. All these risk values are in the range of 10*10–5–100*10–5, which corresponds to the level LOW. For the group of older age patients, the radiation risk was 2.6*10–5, which corresponds to the level of 1*10–5–10*10–5, VERY LOW. Our materials shows in detail the technique to evaluate effective radiation doses for chest CT and calculate the radiation risk of the carcinogenic effects of this exposure.","PeriodicalId":325825,"journal":{"name":"Computed Tomography Scan [Working Title]","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129301822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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