The chapter discusses the principles and techniques of computerized tomographic imaging, focusing on various types of CT scans and their reconstruction algorithms. It begins by explaining the concept of tomography, which involves cross-sectional imaging of an object using transmission or reflection data from multiple angles. The Fourier Slice Theorem is introduced, which states that the one-dimensional Fourier transform of a parallel projection of an image gives a slice of the two-dimensional transform. This theorem is used to derive the filtered backprojection algorithm, which is widely used in medical imaging. The chapter then delves into different types of CT scans, including parallel CT, fanbeam CT, helical CT, and multi-slice CT. Each type has its own advantages and challenges in terms of data acquisition speed, image quality, and reconstruction complexity. Helical CT, introduced around 1990, improves volume coverage speed performance by continuously acquiring data while the patient moves through the gantry. Multi-slice CT, equipped with multiple-row detector arrays, further enhances this performance by allowing simultaneous scanning of multiple slices at different z locations. The chapter also covers the challenges and solutions for improving image quality, such as beam hardening, scatter, and aliasing artifacts. Beam hardening, caused by the photoelectric effect and Compton effect, can be mitigated through preprocessing, postprocessing, or dual-energy techniques. Scatter, which can cause streaks in the reconstructed images, can be reduced by using perfectly collimated detectors or estimating scatter intensity. Aliasing artifacts, which appear as long or thin streaks, can be addressed by increasing the number of samples per projection or the total number of projections. Finally, the chapter discusses other CT applications, such as gated CT for imaging moving objects, angiographic CT for measuring blood flow, emission CT for detecting radioactive isotopes, and ultrasonic CT for soft tissues. It concludes with a discussion on the importance of efficient data acquisition and reconstruction algorithms to improve the overall performance of CT scanners.The chapter discusses the principles and techniques of computerized tomographic imaging, focusing on various types of CT scans and their reconstruction algorithms. It begins by explaining the concept of tomography, which involves cross-sectional imaging of an object using transmission or reflection data from multiple angles. The Fourier Slice Theorem is introduced, which states that the one-dimensional Fourier transform of a parallel projection of an image gives a slice of the two-dimensional transform. This theorem is used to derive the filtered backprojection algorithm, which is widely used in medical imaging. The chapter then delves into different types of CT scans, including parallel CT, fanbeam CT, helical CT, and multi-slice CT. Each type has its own advantages and challenges in terms of data acquisition speed, image quality, and reconstruction complexity. Helical CT, introduced around 1990, improves volume coverage speed performance by continuously acquiring data while the patient moves through the gantry. Multi-slice CT, equipped with multiple-row detector arrays, further enhances this performance by allowing simultaneous scanning of multiple slices at different z locations. The chapter also covers the challenges and solutions for improving image quality, such as beam hardening, scatter, and aliasing artifacts. Beam hardening, caused by the photoelectric effect and Compton effect, can be mitigated through preprocessing, postprocessing, or dual-energy techniques. Scatter, which can cause streaks in the reconstructed images, can be reduced by using perfectly collimated detectors or estimating scatter intensity. Aliasing artifacts, which appear as long or thin streaks, can be addressed by increasing the number of samples per projection or the total number of projections. Finally, the chapter discusses other CT applications, such as gated CT for imaging moving objects, angiographic CT for measuring blood flow, emission CT for detecting radioactive isotopes, and ultrasonic CT for soft tissues. It concludes with a discussion on the importance of efficient data acquisition and reconstruction algorithms to improve the overall performance of CT scanners.