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Multi-Modal Medical Image Fusion Using Laplacian Re-Decomposition
Published in Sarvesh Tanwar, Sumit Badotra, Ajay Rana, Machine Learning, Blockchain, and Cyber Security in Smart Environments, 2023
Kesana Mohana Lakshmi, Suneetha Rikhari
Today, medical image fusion is producing promising results in clinical settings by combining medical images of the same region of interest. This fused information helps medical experts obtain a diagnosis and plan treatment accordingly. Traditionally, medical images have been obtained from different modalities like X-ray, magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), single photon emission computed tomography (SPECT) etc. When wide X-ray beams are passed through the subject, some of these rays reflect back upon hitting the hard tissues of the organs. The reflected rays are then imposed on a photographic film to generate an X-ray image. CT scan images are obtained by subjecting the patient to X-rays at multiple angles to get more detailed information in combination with a computer. CT image provides more detailed information than plain X-rays. CT images provide detailed hard tissue information as compared to soft tissue information. In MRI the patient is kept inside a high magnetic field, and the signal collected from an injection of radio waves is converted into a digital image with a computer. MRI is good at producing soft tissue information, but distorts hard tissue information. Using advanced fusion techniques, the hard and soft tissue information can be fused together into a single image. PET and SPECT modalities come into the category of nuclear medicine. They are used to study circulation and metabolic changes, and can easily detect clots in the heart or brain.
An Efficient System for Predictive Analysis on Brain Cancer Using Machine Learning and Deep Learning Techniques
Published in Teena Bagga, Kamal Upreti, Nishant Kumar, Amirul Hasan Ansari, Danish Nadeem, Designing Intelligent Healthcare Systems, Products, and Services Using Disruptive Technologies and Health Informatics, 2023
Akshita S. Chanchlani, Vilas M. Thakare, Vijay M. Wadhai, Dhanashri H. Gawali, Minakshee Patil
In a CT scan, an x-ray beam circulates around specific part of the body and a series of images are captured from various angles. The computer uses this information to create a series of two-dimensional (2D) cross-sectional image of the organ and combines them to make a three-dimensional (3D) image, which provides a better view of the organs. Positron emission tomography (PET) is a variant of CT where a contrast agent is injected into the body in order to highlight abnormal regions. CT scans are recommended by doctors in many conditions such as hemorrhages, blood clots or cancer. However, CT scans use x-rays which emit ionising radiation and have the potential to affect living tissues, thereby increasing the risk of cancer.
X-ray Vision: Diagnostic X-rays and CT Scans
Published in Suzanne Amador Kane, Boris A. Gelman, Introduction to Physics in Modern Medicine, 2020
Suzanne Amador Kane, Boris A. Gelman
During the CT scan, a series of x-ray projections are collected for different regions of the body. A computer stores these projections, and then mathematically manipulates them to compute a cross section of the body at that plane. Three-dimensional information can then be discerned by either comparing cross sections taken at different points along the body or by having a computer create a three-dimensional image by “stacking up” these cross sections. Since a CT scan really is no more than an elaborate type of x-ray, it is painless.
Computer-aided COVID-19 diagnosis: a possibility?
Published in Journal of Experimental & Theoretical Artificial Intelligence, 2023
Aamir Wali, Shahroze Ali, Asma Naseer, Saira Karim, Zareen Alamgir
RT-PCR test is the formal way to diagnose COVID and it takes almost 24 h using samples taken throat and nose Benmalek et al. (2021). Alternately, since the symptoms include a dry cough and lung infection Huang et al. (2021), an analysis of lung imagery can be crucial for COVID-19 diagnostics. Figure 1 shows sample images of both normal and infected patients’ chest X-ray and computed tomography (CT) scans. CT scan is an imaging procedure that uses rotating X-ray machines to take a series of X-rays images that are later combined to produce cross-sectional images of the body. Although radio-graphic images of patients such as chest X-rays and CT scans are being used to detect COVID, this requires expert radiologists who may not be immediately available, especially in the context of far-flung areas in underdeveloped countries.
An efficient COVID-19 detection from CT images using ensemble support vector machine with Ludo game-based swarm optimisation
Published in Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2022
Shiny Irene D, J. Rene Beulah, Anitha K., Kannan K.
The initial CT image of the lungs in COVID-19 patients offers ground-glass opaque shadows and the ‘crazy paving pattern’ is apparent. The CT scan creates the complete images of soft tissues, blood vessels, bones and organs. The CT images permit the doctors to detect the internal framework and to view their size, density, texture and shape. Dissimilar from the traditional X-rays, the CT scans create the slice sets of the specified body region with no overlaying the various body frameworks (Dong et al. 2020). Hence CT scan provides more detailed image of the patient’s illness than the traditional X-rays. By the worseness of the disease, bilateral lung lesions look like white lungs. Later the lesion density slowly minimises and the lesion area constricts. With respect to the features of the lung CT images of the COVID-19 patients, the disease is classified into four stages namely, primary, progressive, peak and absorption. This complete information is utilised to describe whether there is the clinical issue. For these details, the deep learning techniques are proposed for screening the COVID-19 using CT scans (Kassani et al. 2020).
Overview of the application of inorganic nanomaterials in breast cancer diagnosis
Published in Inorganic and Nano-Metal Chemistry, 2022
Asghar Ashrafi Hafez, Ahmad Salimi, Zhaleh Jamali, Mohammad Shabani, Hiva Sheikhghaderi
Computed tomography scan (CT scan) is a medical imaging method that its earlier name was CAT scan or computed axial tomography. Further, this medical imaging technique is one of the noninvasively methods to achieve images of the body in details as a diagnostic purpose. Additionally, radiology technologists or radiographers perform CT scans. The above versatile imaging technique has developed since 1970s and used in diagnostic medicine. Finally, Allan M. Cormack and Godfrey N. Hounsfield for the development of computer-assisted tomography was awarded jointly the 1979 Nobel Prize in Physiology and Medicine.[58] To compare with other 2D imaging techniques, the X-ray CT technique has three major superiorities. First, the X-ray CT obliterates all of images related to the structures outside the body from internal organs of the body in the desired area. Next, the X-ray CT can diagnose differences among the tissues that differ in physical density by less than 1% because this technique has both high contrast and resolution. The last technique is a multiplanar reformatted imaging and can procure images by multiple contiguous or one helical scan,[59,60] whereas one of the disadvantage of this technique is to use the X-ray beam, which leads to damage the body cell including DNA molecules and this phenomenon might be the cause of cancer in the patient.[61,62] Markedly, allergic reactions and kidney failure to the contrast agents as injected radiocontrast (iodine) intravenous are one of the tricks in these techniques, while the replacement of barium sulfate suspension as oral is a suitable agent to prevent allergic reaction and kidney failure but cannot be used in the patients with suspected bowel perforation or suspected bowel injury.[63]