Oblique reconstructions in tomosynthesis. II. Super‐resolution

Acciavatti, Raymond J.; Maidment, Andrew D. A.

doi:10.1118/1.4819942

Cited by 8 publications

(7 citation statements)

References 33 publications

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“…Similar to previous work, the focal spot is treated as a point in the plane of the chest wall ( y FS = 0), as shown in Fig. by the positioning of the origin (O) along this side of the detector.…”

Section: Resultsmentioning

confidence: 99%

“…In future work, the three‐dimensional (3D) PSF of a DBT reconstruction should be calculated from the 2D PSFs of the projection images. In some DBT systems, the detector rotates during the scan . Detector rotation can be modeled with a different coordinate transformation for point M (Section 2.D.).…”

Section: Discussionmentioning

confidence: 99%

“…In some DBT systems, the detector rotates during the scan. 18,19,[39][40][41] Detector rotation can be modeled with a different coordinate transformation for point M (Section 2.D.). In addition, the 3D PSF should model the reconstruction filter.…”

Section: Discussionmentioning

confidence: 99%

“…, point M is a reference point in the plane z = 0; that is, the midpoint of the chest wall side of the detector. In our previous work, the focal spot coordinates ( x FS and y FS ) were measured relative to this point . In DM, x FS and y FS should be roughly aligned with point M. The exact positioning in a physical system is sensitive to geometric imprecisions.…”

Section: Methodsmentioning

confidence: 99%

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Non‐stationary model of oblique x‐ray incidence in amorphous selenium detectors: I. Point spread function

Acciavatti

Maidment

2019

Medical Physics

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Purpose In previous work, a theoretical model of the point spread function (PSF) for oblique x‐ray incidence in amorphous selenium (a‐Se) detectors was proposed. The purpose of this paper is to develop a complementary model that includes two additional features. First, the incidence angle and the directionality of ray incidence are calculated at each position, assuming a divergent x‐ray beam geometry. This approach allows the non‐stationarity of the PSF to be modeled. Second, this paper develops a framework that is applicable to a digital system, unlike previous work which did not model the presence of a thin‐film transistor (TFT) array. Methods At each point on the detector, the incidence angle and the ray incidence direction are determined using ray tracing. Based on these calculations, an existing model for the PSF of the x‐ray converter (Med Phys. 1995;22:365‐374) is generalized to a non‐stationary model. The PSF is convolved with the product of two rectangle functions, which model the sampling of the TFT array. The rectangle functions match the detector element (del) size in two dimensions. Results It is shown that the PSF can be calculated in closed form. This solution is used to simulate a digital mammography (DM) system at two x‐ray energies (20 and 40 keV). Based on the divergence of the x‐ray beam, the direction of ray incidence varies with position. Along this direction, the PSF is broader than the reference rect function matching the del size. The broadening is more pronounced with increasing obliquity. At high energy, the PSF deviates more strongly from the reference rect function, indicating that there is more blurring. In addition, the PSF is calculated along the polar angle perpendicular to the ray incidence direction. For this polar angle, the shape of the PSF is dependent upon whether the ray incidence direction is parallel with the sides of the detector. If the ray incidence direction is parallel with either dimension, the PSF is a perfect rectangle function, matching the del size. However, if the ray incidence direction is at an oblique angle relative to the sides of the detector, the PSF is not rectangular. These results illustrate the non‐stationarity of the PSF. Conclusions This paper demonstrates that an existing model of the PSF of a‐Se detectors can be generalized to include the effects of non‐stationarity and digitization. The PSF is determined in closed form. This solution offers the advantage of shorter computation time relative to approaches that use numerical methods. This model is a tool for simulating a‐Se detectors in future work, such as in virtual clinical trials with computational phantoms.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Non‐stationary model of oblique x‐ray incidence in amorphous selenium detectors: I. Point spread function

Acciavatti

Maidment

2019

Medical Physics

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“…2 Finally, super-resolution in DBT is feasible independently of the detector used, provided that detector has measurable modulation above the aliasing frequency and the reconstruction algorithm supports finer sampling than the detector in each reconstructed slice. 10 We recognize that there are other additional physical factors such as background noise level, scatter radiation and object attenuation coefficient that can affect the probability of detection of microcalcifications; the sampling, aliasing and 110…”

Section: To the Editor 15mentioning

confidence: 99%

Response to “Comment on ‘Large area CMOS active pixel sensor x‐ray imager for digital breast tomosynthesis: Analysis, modeling, and characterization’ ” [Med. Phys. 43, 1578–1579 (2016)]

2016

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The impact on lesion detection via a multi‐vendor study: A phantom‐based comparison of digital mammography, digital breast tomosynthesis, and synthetic mammography

et al. 2021

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The aim of this study is to perform a test object-based comparison of the imaging performance of digital mammography (DM), digital breast tomosynthesis (DBT), and synthetic mammography (SM). Methods: Two test objects were used, the CDMAM and the L1-structured phantom. Small-detail detectability was assessed using CDMAM and the microcalcification simulating specks in the L1-structured background. Detection of spiculated and non-spiculated mass-like objects was assessed using the L1 phantom. Six different systems were included: Amulet Innovality (Fujifilm), Senographe Pristina (GEHC), 3Dimensions (Hologic), Giotto Class (IMS), Clarity 2D/3D (Planmed), and Mammomat Revelation (Siemens). Images were acquired under automatic exposure control (AEC) and at adjusted levels of AEC/2 and 2 × AEC level. Threshold gold thickness (T tr ) was established for the 0.13-mm-diameter CDMAM discs. Threshold diameters for the calcifications (d tr_c ), the spiculated masses (d tr_sm ), and for the non-spiculated masses (d tr_nsm ) were established. The threshold condition was defined as the thickness or diameter for a 62.5% correct score. Results: T tr for DM was generally superior to DBT, which in turn was superior to SM, but for most systems, these differences between modes were not significant. For L1, no significant differences in d tr_c were found between DM and DBT. The increase in d tr_c from DM to SM at AEC dose was 1%, 19%, 11%, 14%, 46%, and 27% for the Fujifilm, GEHC, Hologic, IMS, Planmed, and Siemens, respectively, indicating significantly poorer performance for all vendors except for Fujifilm, Hologic, and IMS. For both mass types, DBT performed better than SM, while SM showed no significant difference with DM (except for Fujifilm spiculated masses). The dose had an impact on small-detail detectability for both phantoms but did not influence the detection of either mass type. Conclusions: Both phantoms indicated potentially reduced small-detail detectability for SM versus DM and DBT and should therefore not be used in stand-alone mode. The L1 phantom demonstrated no significant difference in microcalcification detection between DM and DBT and also demonstrated the superiority of DBT, compared to DM for mass detection, for all six systems.

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Oblique reconstructions in tomosynthesis. II. Super‐resolution

Abstract: This work provides a platform for investigating super-resolution in oblique reconstructions for tomosynthesis. In breast imaging, this study should have applications in visualizing microcalcifications and other subtle signs of cancer.

Cited by 8 publications

References 33 publications

Non‐stationary model of oblique x‐ray incidence in amorphous selenium detectors: I. Point spread function

Non‐stationary model of oblique x‐ray incidence in amorphous selenium detectors: I. Point spread function

Response to “Comment on ‘Large area CMOS active pixel sensor x‐ray imager for digital breast tomosynthesis: Analysis, modeling, and characterization’ ” [Med. Phys. 43, 1578–1579 (2016)]

The impact on lesion detection via a multi‐vendor study: A phantom‐based comparison of digital mammography, digital breast tomosynthesis, and synthetic mammography

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