What are the three fundamental processes involved in iterative reconstruction algorithms?

Iterative reconstruction algorithms in computed tomography use a systematic approach to refine image quality while minimizing noise and artifacts. The fundamental processes involved are indeed characterized as involving an input, an iterative reconstruction (IR) loop, and the resulting output.

The input phase gathers the raw data collected from the CT scans. This data forms the basis for image reconstruction. The IR loop refers to the iterative process where algorithms continuously adjust and improve the image based on the initial input data. During this loop, the algorithm assesses the image quality, optimizes the projections, and makes iterative adjustments to enhance the final output. The result is the final image produced for diagnostic interpretation, which ideally displays improved clarity and reduced noise compared to conventional methods.

This structured approach in option B specifically highlights the critical role of the iterative loop, which is essential for refining images in iterative reconstruction techniques.