AI RESEARCH
Constructing efficient channels for ideal observers using the conjugate gradient method
arXiv CS.LG
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ArXi:2605.29415v1 Announce Type: cross Task-based assessment of image quality (IQ) is critically important for the design and optimization of medical imaging systems. Ideal observers, including the Bayesian Ideal Observer (IO) and the ideal linear observer, i.e., the Hotelling observer (HO), provide objective figures of merit (FOMs) that quantify system performance on signal detection tasks. However, the application of ideal observers to high-dimensional image data is often computationally intractable.