Detector for dual-energy digital radiography.

Barnes, Gary T.; Sones, R. A.; Tesic, M M; Morgan, Douglas R.; Sanders, John N.

doi:10.1148/radiology.156.2.4011921

Cited by 80 publications

(54 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The analysis of this 4D data leads to methods for digital-spirometry, a potential for revolutionizing the radiotherapy treatment for the thorax and upper abdomen. The next article burst is ''Detector for dualenergy digital radiography'' by Barnes (1985). In their experiment, they separated the X-ray beam transmitted into low and high energy components by an atomic number detector and resulted in improved energy separation and lower noise levels.…”

Section: Emerging Trends and Research Front Of Digital Medicinementioning

confidence: 99%

See 1 more Smart Citation

Visualizing the structure and the evolving of digital medicine: a scientometrics review

Fang

2015

Scientometrics

View full text Add to dashboard Cite

This article aims to analyze and visualize the structure and the emerging trend of digital medicine, a new medical pattern of twenty-first century. Our study objectively explores the document co-citation clusters of 6060 bibliographic records to identify the origin of digital medicine and the hot research specialty of domain. Pivotal point articles, prominent authors, active disciplines and institution have been identified by network analysis theory. CiteSpace was used to visualize the perspective of digital medicine domain. As an interdiscipline which integrated computer science, information engineering with medicine, digital medicine originally and mainly on digital medical imaging technology research for accuracy and speedy clinical diagnosis and therapy. Of 6060 relevant records reviewed, 1719 (28 %) are on radiology, 902 (15 %) are on engineering, 539 (9 %) are on computer science. The largest co-citation cluster is on digital tomosynthesis. The earliest cluster is on medical imaging segmentation and registration. Post-processing imaging technology, detector, phase contrast, reversible watermarking, input, model 3D reconstruct, real-time dynamic imaging, dosimetry have been the hot research topics. The recently cluster is on internet health information. Harvard University of USA is the prominent institution. The coverage of digital medicine research is widely from clinic to laboratory. Recent year, domain research front is thematically on teleradiology, telemedicine and hospital information management system.

show abstract

Section: Emerging Trends and Research Front Of Digital Medicinementioning

confidence: 99%

“…Compared with commonly used dual-energy detector at that time, it's a promising method for digital scanned projection radiography. Both articles focus on post-processing imaging especially real-time dynamic imaging (Low et al 2003;Barnes et al 1985).…”

Section: Emerging Trends and Research Front Of Digital Medicinementioning

confidence: 99%

Visualizing the structure and the evolving of digital medicine: a scientometrics review

Fang

2015

Scientometrics

View full text Add to dashboard Cite

show abstract

“…Calibration was obtained from one phantom of 14 cm in diameter. This one-point calibration was used to decompose breast sizes of 8,10,12,14,16,18, and 20 cm in diameter. As seen from the graphs, measurements were more accurate in the vicinity of 14 cm.…”

Section: Resultsmentioning

confidence: 99%

“…9 The double-layered detector method acquires x-ray signals simultaneously with a front and a rear detector that are sandwiched together. 10 In dual-source CT system, two x-ray tubes and two detectors are positioned orthogonal to each other for dual energy scanning. 8 The major disadvantage of both the kVp switching and the dual-source methods is the misregistration between high and low energy data.…”

Section: Introductionmentioning

confidence: 99%

Least squares parameter estimation methods for material decomposition with energy discriminating detectors

Lê

Molloi

2010

Medical Physics

View full text Add to dashboard Cite

Purpose: Energy resolving detectors provide more than one spectral measurement in one image acquisition. The purpose of this study is to investigate, with simulation, the ability to decompose four materials using energy discriminating detectors and least squares minimization techniques. Methods: Three least squares parameter estimation decomposition techniques were investigated for four-material breast imaging tasks in the image domain. The first technique treats the voxel as if it consisted of fractions of all the materials. The second method assumes that a voxel primarily contains one material and divides the decomposition process into segmentation and quantification tasks. The third is similar to the second method but a calibration was used. The simulated computed tomography ͑CT͒ system consisted of an 80 kVp spectrum and a CdZnTe ͑CZT͒ detector that could resolve the x-ray spectrum into five energy bins. A postmortem breast specimen was imaged with flat panel CT to provide a model for the digital phantoms. Hydroxyapatite ͑HA͒ ͑50, 150, 250, 350, 450, and 550 mg/ml͒ and iodine ͑4, 12, 20, 28, 36, and 44 mg/ml͒ contrast elements were embedded into the glandular region of the phantoms. Calibration phantoms consisted of a 30/70 glandular-toadipose tissue ratio with embedded HA ͑100, 200, 300, 400, and 500 mg/ml͒ and iodine ͑5, 15, 25, 35, and 45 mg/ml͒. The x-ray transport process was simulated where the Beer-Lambert law, Poisson process, and CZT absorption efficiency were applied. Qualitative and quantitative evaluations of the decomposition techniques were performed and compared. The effect of breast size was also investigated. Results: The first technique decomposed iodine adequately but failed for other materials. The second method separated the materials but was unable to quantify the materials. With the addition of a calibration, the third technique provided good separation and quantification of hydroxyapatite, iodine, glandular, and adipose tissues. Quantification with this technique was accurate with errors of 9.83% and 6.61% for HA and iodine, respectively. Calibration at one point ͑one breast size͒ showed increased errors as the mismatch in breast diameters between calibration and measurement increased. A four-point calibration successfully decomposed breast diameter spanning the entire range from 8 to 20 cm. For a 14 cm breast, errors were reduced from 5.44% to 1.75% and from 6.17% to 3.27% with the multipoint calibration for HA and iodine, respectively. Conclusions:The results of the simulation study showed that a CT system based on CZT detectors in conjunction with least squares minimization technique can be used to decompose four materials. The calibrated least squares parameter estimation decomposition technique performed the best, separating and accurately quantifying the concentrations of hydroxyapatite and iodine.

show abstract

“…Brooks and Di Chiro [8] and Fenster [9] investigated a xenon split-detector design for CT. Barnes et al. [10] demonstrated single-shot images using a pair of scintillator-coupled linear photodiode arrays that required a time-consuming scanning procedure for area images. More recently, Allec et al [11] reported on the feasibility of using amorphous-selenium layers.…”

Section: Introductionmentioning

confidence: 99%

Single-shot dual-energy x-ray imaging with a flat-panel sandwich detector for preclinical imaging

Han

Kim

et al. 2014

Current Applied Physics

View full text Add to dashboard Cite

Detector for dual-energy digital radiography.

Cited by 80 publications

References 0 publications

Visualizing the structure and the evolving of digital medicine: a scientometrics review

Visualizing the structure and the evolving of digital medicine: a scientometrics review

Least squares parameter estimation methods for material decomposition with energy discriminating detectors

Single-shot dual-energy x-ray imaging with a flat-panel sandwich detector for preclinical imaging

Contact Info

Product

Resources

About