Technical Note: The nearest neighborhood‐based approach for estimating basis line‐integrals using photon‐counting detector. Issue 10 (25th June 2021)

• Record Type: Journal Article
• Authors: Nam, Jeonghyeon; Lee, Okkyun
• Is Part Of: Medical physics. Volume 48:Issue 10(2021)
• Page Start: 6531
• Page End: 6535
• Publication Date: 2021-06-25
• Subjects: k‐d tree -- maximum likelihood -- nearest neighbor -- photon‐counting detector; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1002/mp.14920
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: This study aims to develop a calibration‐based estimator for the photon‐counting detector (PCD)‐based x‐ray computed tomography. Methods: We propose the nearest neighborhood (NN)‐based estimator, which searches for the nearest calibration data for a given PCD output and sets the associated basis line‐integrals as the estimate. Searching for the nearest neighbors can be accelerated using the pre‐calculated k ‐d tree for the data. Results: The proposed method is compared to the model‐based maximum likelihood (ML) estimator. For slab phantom study, both ML and NN‐based methods achieve the Cramér‐Rao lower bound and are unbiased for various combinations of three basis materials (water, bone, and gold). The proposed method is also validated for K‐edge imaging and presents almost unbiased Au concentrations in the region of interest. Conclusions: The proposed NN‐based method is demonstrated to be as accurate as the model‐based ML estimator, but it is computationally efficient and requires only calibration measurements.