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PET is the latest imaging method with a wide variety of medical uses. In 1975, the first commercial PET scanner was introduced, and in the 1990s it was used in clinics regularly. PET is a type of nuclear imaging method which produces a 3D image of the biological process in the human body by measuring the radiation emitted by photons. Finally, the sinogram is implemented using an image reconstruction algorithm, generating a tomography representation of the patient body. This image is called a sinogram and is the most common source of raw CT scanning data for organizations. If the camera system is done spinning, all the one-dimensional projections are spliced, making a picture that looks like multiple superimposed sinusoidal pictures.
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The data from the projection are recorded during this process. While the X-ray source is spinning, sensors record the scanned patient’s one-dimensional projection. In the meantime, X-ray detectors are located in a field on the other side. Then it activates the X-ray source and rotates around the patient. The CT system then moves the patient to find the right location for the scanning. The core principles of the X-ray computed tomography involve X-ray generation, processing, identification, digitization, and image reconstruction which can be used to represent and analyze objects without physical harm, which provides several advantages in relevant areas.įirst, it illustrates a standard procedure of a medical CT scan the patient is to lie on a hospital bed. CT eliminates the superimposition of pictures of an object outside the field of interest. CT has become an effective method for supplementing X-rays and ultrasonography in medical imaging. It is the most popular modality used in clinical diagnosis to detect abnormalities such as cancer, tumors, or organ deficiencies. The CT system is typically calculated by the X-ray source, detector, and scanning direction.
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Computed Tomography (CT)ĬT is a method of measuring an object’s cross-sections using a series of X-ray measurements taken around the body from various angles. There are several medical imaging modalities like “computed tomography (CT), Ultrasound, Positron Emission Tomography (PET), Single-Photon Emission Computed Tomography (SPECT), Optical Coherence Tomography (OCT), Mammography, Magnetic Resonance Imaging (MRI), and Microwave Imaging” and so forth, as illustrated in Figure 1. More tests are to be conducted to detect changes in the heart rate, blood supply, chemical composition, and blood absorption these days because of the usefulness of imaging devices. These modalities enable the radiologist to acquire a perfect spatial resolution in a noninvasive manner, typically providing the three-dimensional view of the anatomical and functional behaviour of the internal structure of human bodies like the heart, kidney, liver, and spleen. Currently, in medical imaging, a wide number of different image modalities are used. Medical imaging offers a noninvasive technique to look at the practical and structural information of internal organs. As far as we know, no previous work examined this issue. Finally, based on comparative analysis, the possible research strategies for further development are proposed. We also studied and compared each approach used for other imaging modalities based on the certain parameter used for the system evaluation. This paper discusses various medical imaging modalities and presents a short review of soft computing approaches such as fuzzy logic, artificial neural network, genetic algorithm, machine learning, and deep learning. Until now, various soft computing approaches have been proposed for medical applications. It handles uncertainties and improves the qualities of an image. Soft computing plays a major role in the recent advances in medical imaging. Medical imaging is an essential technique for the diagnosis and treatment of diseases in modern clinics.