Heel effect adaptive flat field correction of digital x-ray detectors

Yu, Yongjian; Wang, Jue

doi:10.1118/1.4813303

Cited by 9 publications

(7 citation statements)

References 9 publications

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“…In radiography, the heel effect causes less X-ray fluence and higher mean radiation energy in the anode direction, and results in non-uniform image quality. Although there have been some methods proposed to reduce the heel effect [ 19 , 20 , 21 ], no suitable method has been presented that can objectively quantify the overall and non-uniform image quality caused by the heel effect. This study designed a CSW phantom for quantification of overall and non-uniform image quality in X-ray radiographs using nMI metrics based on information theory.…”

Section: Discussionmentioning

confidence: 99%

“…Previous studies demonstrated that the heel effect significantly impacted the signal-to-noise ratio (SNR) using an anthropomorphic phantom, but the image quality was not significantly different between pelvic radiographs with the head towards the anode and cathode directions [ 17 , 18 ]. Moreover, some previous studies performed post-processing heel effect correction (HEC) to minimize the inhomogeneous intensity in radiographs [ 19 , 20 , 21 ]. However, no suitable method has been presented that can objectively quantify the non-uniform image quality in radiographs.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of Non-Uniform Image Quality Caused by Anode Heel Effect in Digital Radiography Using Mutual Information

Chou

2021

Entropy

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Anode heel effects are known to cause non-uniform image quality, but no method has been proposed to evaluate the non-uniform image quality caused by the heel effect. Therefore, the purpose of this study was to evaluate non-uniform image quality in digital radiographs using a novel circular step-wedge (CSW) phantom and normalized mutual information (nMI). All X-ray images were acquired from a digital radiography system equipped with a CsI flat panel detector. A new acrylic CSW phantom was imaged ten times at various kVp and mAs to evaluate overall and non-uniform image quality with nMI metrics. For comparisons, a conventional contrast-detail resolution phantom was imaged ten times at identical exposure parameters to evaluate overall image quality with visible ratio (VR) metrics, and the phantom was placed in different orientations to assess non-uniform image quality. In addition, heel effect correction (HEC) was executed to elucidate the impact of its effect on image quality. The results showed that both nMI and VR metrics significantly changed with kVp and mAs, and had a significant positive correlation. The positive correlation is suggestive that the nMI metrics have a similar performance to the VR metrics in assessing the overall image quality of digital radiographs. The nMI metrics significantly changed with orientations and also significantly increased after HEC in the anode direction. However, the VR metrics did not change significantly with orientations or with HEC. The results indicate that the nMI metrics were more sensitive than the VR metrics with regards to non-uniform image quality caused by the anode heel effect. In conclusion, the proposed nMI metrics with a CSW phantom outperformed the conventional VR metrics in detecting non-uniform image quality caused by the heel effect, and thus are suitable for quantitatively evaluating non-uniform image quality in digital radiographs with and without HEC.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluation of Non-Uniform Image Quality Caused by Anode Heel Effect in Digital Radiography Using Mutual Information

Chou

2021

Entropy

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“…It should be noted that the heel effect is corrected only for the gain-map composition and not for clinical images, which implies that intrinsic heel effect remains in clinical images even after the gain and offset correction. Regarding moving geometry, Yu and Wang 13 recently introduced a novel method to correct the heel effect for gain calibration in an SID-variant environment. Compared to their work, gain calibration for our system has different challenges, including 2D DOF of panel movement and the existence of the intrinsic obstacle.…”

Section: Discussionmentioning

confidence: 99%

Gain Correction for an X-ray Imaging System With a Movable Flat Panel Detector and Intrinsic Localization Crosshair

Park

Sharp

2015

Technol Cancer Res Treat

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Gain calibration for X-ray imaging systems with a movable flat panel detector and an intrinsic crosshair is a challenge due to the geometry-dependent heel effect and crosshair artifact. This study aims to develop a gain correction method for such systems by implementing the Multi-Acquisition Gain Image Correction technique. Flood field images containing crosshair and heel effect were acquired in 4 different flat panel detector positions at fixed exposure parameters. The crosshair region was automatically detected using common image processing algorithms and removed by a simple interpolation procedure, resulting in a crosshair-removed image. A large kernel-based correction was then used to remove the heel effect. Mask filters corresponding to each crosshair region were applied to the resultant heel effect-removed images to invalidate the pixels of the original crosshair region. Finally, a seamless gain map was composed with corresponding valid pixels from the processed images either by the sequential replacement or by the selective averaging techniques developed in this study. Quantitative evaluation was performed based on normalized noise power spectrum and detective quantum efficiency improvement factor for the flood field images corrected by the MultiAcquisition Gain Image Correction-based gain maps. For comparison purposes, a single crosshair-removed gain map was also tested. As a result, it was demonstrated that the Multi-Acquisition Gain Image Correction technique achieved better image quality than the crosshair-removed technique, showing lower normalized noise power spectrum values over most of spatial frequencies. The improvement was more obvious at the priori-crosshair region of the gain map. The mean detective quantum efficiency improvement factor was 1.09 + 0.06, 2.46 + 0.32, and 3.34 + 0.36 in the priori-crosshair region and 2.35 + 0.31, 2.33 + 0.31, and 3.09 + 0.34 in the normal region, for crosshair-removed, Multi-Acquisition Gain Image Correction-sequential replacement, and Multi-Acquisition Gain Image Correction-selective averaging techniques, respectively. Therefore, this study indicates that the introduced Multi-Acquisition Gain Image Correction technique is an appropriate method for gain calibration of an imaging system associated with a moving flat panel detector and an intrinsic crosshair.

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“…In Fig. 12(b), because the vignetting parts still have faint images, we can use a flat-field correction (FFC) method to correct these parts [25]. After that, we trim the partial images.…”

Section: Image Processingmentioning

confidence: 99%

Wide-angle and ultrathin camera module using a curved hexagonal microlens array and all spherical surfaces

Liang

2014

Appl. Opt.

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In this paper, we propose a wide-angle and thin camera module integrating the principles of an insect's compound eye and the human eye, mimicking them with a curved hexagonal microlens array and a hemispherical lens, respectively. Compared to typical mobile phone cameras with more than four lenses and a limited full field of view (FFOV), the proposed system uses only two lenses to achieve a wide FFOV. Furthermore, the thickness of our proposed system is only 2.7 mm. It has an f-number of 2.07, an image diameter of 4.032 mm, and a diagonal FFOV of 136°. The results showed good image quality with a modulation transfer function above 0.3 at a Nyquist frequency of 166 cycles/mm.

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Heel effect adaptive flat field correction of digital x-ray detectors

Cited by 9 publications

References 9 publications

Evaluation of Non-Uniform Image Quality Caused by Anode Heel Effect in Digital Radiography Using Mutual Information

Evaluation of Non-Uniform Image Quality Caused by Anode Heel Effect in Digital Radiography Using Mutual Information

Gain Correction for an X-ray Imaging System With a Movable Flat Panel Detector and Intrinsic Localization Crosshair

Wide-angle and ultrathin camera module using a curved hexagonal microlens array and all spherical surfaces

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