Image Reconstruction Theory

Image Reconstruction Theory involves generating a complete image from incomplete or indirect data, such as signals or measurements. It relies on mathematical techniques to infer missing information, allowing us to create clear visual representations from limited or noisy sources. Common applications include medical imaging (like MRI or CT scans), where it helps construct detailed images of internal structures, and tomography. The theory balances data accuracy with computational efficiency, using algorithms to optimize the reconstructed image, ensuring it accurately reflects the true scene or object despite initial data limitations.