&lt;title&gt;New automatic tone-scale method for computed radiography&lt;/title&gt;

Barski, Lori L.; Metter, Richard L. Van; Foos, David H.; Lee, Hsien-Che; Wang, Xiaohui

doi:10.1117/12.312489

Cited by 11 publications

(5 citation statements)

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“…However, it appears questionable that this additional effort would be accepted for routine post-processing in a busy radiological department. In clinical practice, image processing methods with automatic tone scale rendering and latitude and contrast enhancement are rather welcome for producing display ready hardcopies or minimizing the time required for image manipulation during softcopy reading [3,13,18,[32][33][34]. These effects on clinical work flow were documented recently [35].…”

Section: Clinical Relevancementioning

confidence: 96%

“…al [16] and Blume [17]. The essential elements of the algorithm; image analysis, tone scale generation, and tone scale application, produce a displayready image that is similar in appearance to optimum screen-film imaging [18]. The display-ready image is computed with eq.…”

Section: Simulation Of Pulmonary Nodulesmentioning

confidence: 99%

“…A p-value of 0.05 was defined as statistically significant. The sample size of 80 normal-abnormal case pairs for the second series was estimated as suggested by H. Kundel to allow for receiver operating characteristic (ROC) analysis [18]. Calculations were made with standard software (Excel 97, Microsoft, Redmond, WA, USA; SSPS, 10.0).…”

Section: Statisticsmentioning

confidence: 99%

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Pulmonary nodule detection with digital projection radiography: an ex-vivo study on increased latitude post-processing

et al. 2006

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To evaluate increased image latitude post-processing of digital projection radiograms for the detection of pulmonary nodules. 20 porcine lungs were inflated inside a chest phantom, prepared with 280 solid nodules of 4-8 mm in diameter and examined with direct radiography (3.0x2.5 k detector, 125 kVp, 4 mAs). Nodule position and size were documented by CT controls and dissection. Four intact lungs served as negative controls. Image post-processing included standard tone scales and increased latitude with detail contrast enhancement (log-factors 1.0, 1.5 and 2.0). 1280 sub-images (512x512 pixel) were centred on nodules or controls, behind the diaphragm and over free parenchyma, randomized and presented to six readers. Confidence in the decision was recorded with a scale of 0-100%. Sensitivity and specificity for nodules behind the diaphragm were 0.87/0.97 at standard tone scale and 0.92/0.92 with increased latitude (log factor 2.0). The fraction of "not diagnostic" readings was reduced (from 208/1920 to 52/1920). As an indicator of increased detection confidence, the median of the ratings behind the diaphragm approached 100 and 0, respectively, and the inter-quartile width decreased (controls: p<0.001, nodules: p=0.239) at higher image latitude. Above the diaphragm, accuracy and detection confidence remained unchanged. Here, the sensitivity for nodules was 0.94 with a specificity from 0.96 to 0.97 (all p>0.05). Increased latitude post-processing has minimal effects on the overall accuracy, but improves the detection confidence for sub-centimeter nodules in the posterior recesses of the lung.

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Section: Clinical Relevancementioning

confidence: 96%

Section: Simulation Of Pulmonary Nodulesmentioning

confidence: 99%

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Pulmonary nodule detection with digital projection radiography: an ex-vivo study on increased latitude post-processing

et al. 2006

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“…To reconstruct the image P 0 and P 1 frequencies are boosted by a factor of 1.5, while P 3 to P 8 frequencies are reduced by a factor 2 * 0.5 (i−1) . Afterwards, a s-shaped LUT is applied similar to [25,26]. With radiograph intensities normalized between 0 and 8, left clip is set at 1.5 and right clip at 7.5.…”

Section: G Postprocessingmentioning

confidence: 99%

Per-Pixel Lung Thickness and Lung Capacity Estimation on Chest X-Rays using Convolutional Neural Networks

Schultheiß¹,

Schmette²,

Sellerer³

et al. 2021

Preprint

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Estimating the lung depth on x-ray images could provide both an accurate opportunistic lung volume estimation during clinical routine and improve image contrast in modern structural chest imaging techniques like x-ray dark-field imaging. We present a method based on a convolutional neural network that allows a per-pixel lung thickness estimation and subsequent total lung capacity estimation. The network was trained and validated using 5250 simulated radiographs generated from 525 real CT scans. Furthermore, we are able to infer the model trained with simulation data on real radiographs.For 35 patients, quantitative and qualitative evaluation was performed on standard clinical radiographs. The ground-truth for each patient's total lung volume was defined based on the patients' corresponding CT scan. The mean-absolute error between the estimated lung volume on the 35 real radiographs and groundtruth volume was 0.73 liter. Additionaly, we predicted the lung thicknesses on a synthetic dataset of 131 radiographs, where the mean-absolute error was 0.27 liter. The results show, that it is possible to transfer the knowledge obtained in a simulation model to real x-ray images.

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“…It is based on a "perceptually linear" tone scale that properly incorporates the characteristics of the human visual system [16 -18]. The essential elements of the algorithm, i. e., image analysis, tone scale generation, and tone scale application, produce a display-ready image that is similar in appearance to optimum screen-film imaging [19]. The purpose of enhanced visualization processing (EVP) is to increase the latitude of radiographic images while preserving or enhancing the contrast of image detail.…”

Section: Computed Tomography and Documentation Of Findingsmentioning

confidence: 99%

Detection of Artificial Air Space Opacities with Digital Radiography: Ex Vivo Study on Enhanced Latitude Post-Processing

Biederer

Bolte²,

Schmidt³

et al. 2010

Fortschr Röntgenstr

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<title>New automatic tone-scale method for computed radiography</title>

Cited by 11 publications

References 0 publications

Pulmonary nodule detection with digital projection radiography: an ex-vivo study on increased latitude post-processing

Pulmonary nodule detection with digital projection radiography: an ex-vivo study on increased latitude post-processing

Per-Pixel Lung Thickness and Lung Capacity Estimation on Chest X-Rays using Convolutional Neural Networks

Detection of Artificial Air Space Opacities with Digital Radiography: Ex Vivo Study on Enhanced Latitude Post-Processing

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