One-shot dual-energy subtraction imaging.

Ishigaki, Takashi; Sakuma, S; Horikawa, Yo; Ikeda, Mitsuru; Yamaguchi, Hiroya

doi:10.1148/radiology.161.1.3532182

Cited by 75 publications

(40 citation statements)

References 1 publication

(1 reference statement)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…One method used for image processing is the energy subtraction method [1]. This involves acquiring images at two different x-ray energies:…”

Section: Discussionmentioning

confidence: 99%

“…Low energy information is obtained from the imaging plate in front of a copper plate. High energy information is obtained from the imaging plate in back of the copper plate, as the metal filters out the low energy information [1][2][3][4].…”

Section: Discussionmentioning

confidence: 99%

“…This one-shot energy subtraction method [1][2][3][4], which has already been 2 effectively used in chest radiography, is one of several image processing technologies. The one-shot energy subtraction method is a unique kind of image processing.…”

Section: Introductionmentioning

confidence: 99%

“…The one-shot energy subtraction method is a unique kind of image processing. Using the energy absorption characteristics differences between bones and soft tissues in the chest, bone images and soft tissue images are visualized separately [1]. The one-shot energy subtraction method has already been effectively used for a wide range of clinical applications with chest images comprised of soft tissue only [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

The clinical utility of a one-shot energy subtraction method for thoracic spine radiography

Sasagawa

Kunogi

Masuyama

et al. 2012

Journal of Orthopaedic Science

View full text Add to dashboard Cite

show abstract

“…One method used for image processing is the energy subtraction method [1]. This involves acquiring images at two different x-ray energies:…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The clinical utility of a one-shot energy subtraction method for thoracic spine radiography

Sasagawa

Kunogi

Masuyama

et al. 2012

Journal of Orthopaedic Science

View full text Add to dashboard Cite

show abstract

“…Despite recent developments in CT techniques, difficulties remain, such as shifting of the slice level in thin-section CT images acquired during different breaths, and difficulty in clarifying the characteristics and distribution of calcifications relative to soft tissue components of the mass. Dual-energy digital radiography has been found useful in detecting calcifications [6,9,[15][16][17][18]. Projection images acquired using DES techniques, however, suffer from the problem of overlap of anatomic features (e.g., calcifications superimposed over the ribs or spine).…”

Section: Introductionmentioning

confidence: 99%

Comparison of Chest Dual-Energy Subtraction Digital Tomosynthesis and Conventional Digital Tomosynthesis for the Detection of Simulated Pulmonary Nodules with Calcifications: Phantom Study

Gomi

Nakajima²,

Fujiwara³

2011

TOMIJ

View full text Add to dashboard Cite

Abstract:To compare the effectiveness of chest dual-energy subtraction digital tomosynthesis (DES-DT) with that of conventional digital tomosynthesis for the detection of calcifications superimposed over simulated pulmonary nodules. A DES-DT system with pulsed X-rays and rapid kV switching was used to examine calcifications in simulated pulmonary nodules. Low-voltage, high-voltage, and soft-tissue or bone-subtracted tomograms of the desired layer thicknesses were reconstructed from the image data acquired during a single tomographic scan, bone-subtracted images, and a scan angle of 40°. Our analysis took into account the signal-to-noise ratio (SNR) of the different degrees of calcification in the simulated pulmonary nodules. For DES-DT, the SNR for the simulated pulmonary nodules increased about 63%. Based on the results of receiver operating characteristic performance analysis, the detection ability of our DES-DT was significantly better than that of conventional digital tomosynthesis (P < 0.03). The study results confirmed with a further study to assess influence of reconstruction and filtering for detection of simulated nodules. DES-DT provided greater sensitivity than conventional digital tomosynthesis.

show abstract

Separation of bones from soft tissue in chest radiographs: Anatomy‐specific orientation‐frequency‐specific deep neural network convolution

et al. 2019

View full text Add to dashboard Cite

Purpose Lung nodules that are missed by radiologists as well as by computer‐aided detection (CAD) systems mostly overlap with ribs and clavicles. Removing the bony structures would result in better visualization of undetectable lesions. Our purpose in this study was to develop a virtual dual‐energy imaging system to separate ribs and clavicles from soft tissue in chest radiographs. Methods We developed a mixture of anatomy‐specific, orientation‐frequency‐specific (ASOFS) deep neural network convolution (NNC) experts. Anatomy‐specific (AS) NNC was designed to separate the bony structures from soft tissue in different lung segments. While an AS design was proposed previously under our massive‐training artificial neural networks (MTANN) framework, in this work, we newly mathematically defined an AS experts model as well as its learning and inference strategies in a probabilistic deep‐learning framework. In addition, in combination with our AS experts design, we newly proposed the orientation‐frequency‐specific (OFS) NNC models to decompose bone and soft‐tissue structures into specific orientation‐frequency components of different scales using a multi‐resolution decomposition technique. We trained multiple NNC models, each of which is an expert for a specific orientation‐frequency component in a particular anatomic segment. Perfect reconstruction discrete wavelet transform was used for OFS decomposition/reconstruction, while we introduced a soft‐gating layer to merge the predictions of AS NNC experts. To train our model, we used the bone images obtained from a dual‐energy system as the target (or teaching) images while the standard chest radiographs were used as the input to our model. The training, validation, and test were performed in a nested two‐fold cross‐validation manner. Results We used a database of 118 chest radiographs with pulmonary nodules to evaluate our NNC scheme. In order to evaluate our scheme, we performed quantitative and qualitative evaluation of the predicted bone and soft‐tissue images from our model as well as the ones of a state‐of‐the‐art technique where the “gold‐standard” dual‐energy bone and soft‐tissue images were used as the reference images. Both quantitative and qualitative evaluations demonstrated that our ASOFS NNC was superior to the state‐of‐the‐art bone‐suppression technique. Particularly, our scheme was better able to maintain the conspicuity of nodules and lung vessels, comparing to the reference technique, while it separated ribs and clavicles from soft tissue. Comparing to a state‐of‐the‐art bone suppression technique, our bone images had substantially higher (t−test; P < 0.01) similarity, in terms of structural similarity index (SSIM) and peak signal‐to‐noise ratio (PSNR), to the “gold−standard” dual−energy bone images. Conclusions Our deep ASOFS NNC scheme can decompose chest radiographs into their bone and soft‐tissue images accurately, offering the improved conspicuity of lung nodules and vessels, and therefore would be useful for radiologists as well as CAD systems in d...

show abstract

One-shot dual-energy subtraction imaging.

Cited by 75 publications

References 1 publication

The clinical utility of a one-shot energy subtraction method for thoracic spine radiography

The clinical utility of a one-shot energy subtraction method for thoracic spine radiography

Comparison of Chest Dual-Energy Subtraction Digital Tomosynthesis and Conventional Digital Tomosynthesis for the Detection of Simulated Pulmonary Nodules with Calcifications: Phantom Study

Separation of bones from soft tissue in chest radiographs: Anatomy‐specific orientation‐frequency‐specific deep neural network convolution

Contact Info

Product

Resources

About