arXiv subjects

Joyoni Dey

Publications and source records attributed to Joyoni Dey.

7 recordsLinked to original sources

arXiv2026

Range of Normalized Glandular Dose for Mammography Using Patient-Specific Glandular Fractions

Breast cancer is the most common cancer among women, and mammography remains the primary modality for early detection. Because mammography uses ionizing radiation, accurate estimation of normalized glandular dose (DgN) is important for risk assessment. Recent breast dosimetry models, including TG-282, incorporate population-based glandular tissue distributions; however, patient-specific glandular distributions remain unknown from conventional mammographic projections. In previous work (Smith, Dey et al., 2025), glandular fraction (GF) maps were estimated from a single mammographic projection. While these maps determine glandular path length along each projection ray, they do not uniquely define glandular tissue depth. In this work, we propose a framework for estimating a patient-specific range of DgN from a projection-derived GF map. Using simulated data, glandular tissue was distributed to the top, center, and bottom of the breast volume using Siddon ray-tracing. These configurations preserved the GF map while producing maximum, intermediate, and minimum DgN values. Monte Carlo simulations were performed, and DgN was normalized to entrance air kerma. DgN varied by up to a factor of three solely due to differences in glandular tissue depth, despite identical GF maps and visually indistinguishable projection images. Using randomized realizations derived from TG-282 glandular distributions for Cranio-Caudal (CC) and Medio-Lateral Oblique (MLO) views, dose ratios were calculated relative to central glandular placement. Central placement overestimated DgN by less than 5 and 15 percent on average for MLO and CC distributions respectively, whereas centroid-based placement underestimated dose by up to 25 percent. These results indicate that patient-specific bounds on DgN can be estimated from limited mammographic information and that central placement provides a conservative dose estimate.

physics.med-ph↗

arXiv2025

Dark-Field X-Ray Imaging Significantly Improves Deep-Learning based Detection of Synthetic Early-Stage Lung Tumors in Preclinical Models

Low-dose computed tomography (LDCT) is the current standard for lung cancer screening, yet its adoption and accessibility remain limited. Many regions lack LDCT infrastructure, and even among those screened, early-stage cancer detection often yield false positives, as shown in the National Lung Screening Trial (NLST) with a sensitivity of 93.8 percent and a false-positive rate of 26.6 percent. We aim to investigate whether X-ray dark-field imaging (DFI) radiograph, a technique sensitive to small-angle scatter from alveolar microstructure and less susceptible to organ shadowing, can significantly improve early-stage lung tumor detection when coupled with deep-learning segmentation. Using paired attenuation (ATTN) and DFI radiograph images of euthanized mouse lungs, we generated realistic synthetic tumors with irregular boundaries and intensity profiles consistent with physical lung contrast. A U-Net segmentation network was trained on small patches using either ATTN, DFI, or a combination of ATTN and DFI channels. Results show that the DFI-only model achieved a true-positive detection rate of 83.7 percent, compared with 51 percent for ATTN-only, while maintaining comparable specificity (90.5 versus 92.9 percent). The combined ATTN and DFI input achieved 79.6 percent sensitivity and 97.6 percent specificity. In conclusion, DFI substantially improves early-tumor detectability in comparison to standard attenuation radiography and shows potential as an accessible, low-cost, low-dose alternative for pre-clinical or limited-resource screening where LDCT is unavailable.

physics.med-ph↗

arXiv2025

Moir\'e Artifact Reduction in Grating Interferometry Using Multiple Harmonics and Total Variation Regularization

X-ray interferometry is an emerging imaging modality with a wide variety of potential clinical applications, including lung imaging. A grating interferometer uses a diffraction grating to produce a periodic interference pattern and measures how a patient or sample perturbs the pattern, producing three unique images that highlight X-ray absorption, refraction, and small angle scattering, known as the attenuation, differential-phase, and dark-field images, respectively. Inaccuracies in grating position and multi-harmonic fringes produce Moir\'e artifacts when assuming the fringe pattern is perfectly sinusoidal and the phase steps are evenly spaced. We have developed an image recovery algorithm that estimates the true phase stepping positions using multiple harmonics and total variation regularization, removing the Moir\'e artifacts present in the attenuation, differential-phase, and dark-field images. We demonstrate the algorithm's utility for the Talbot-Lau and Modulated Phase Grating Interferometers by imaging multiple samples, including PMMA microspheres and a euthanized mouse.

physics.optics↗

arXiv2025

Reducing Artifacts in Grating Interferometry Using Multiple Harmonics and Phase Step Corrections

X-ray interferometry is an emerging imaging modality with a wide variety of potential clinical applications, including lung and breast imaging, as well as in non-destructive testing, such as additive manufacturing and porosimetry. A grating interferometer uses a diffraction grating to produce a periodic interference pattern and measures how a patient or sample perturbs the pattern, producing three unique images that highlight X-ray absorption, refraction, and small angle scattering, known as the transmission, differential-phase, and dark-field images, respectively. Image artifacts that are unique to X-ray interferometry are introduced when assuming the fringe pattern is perfectly sinusoidal and the phase steps are evenly spaced. Inaccuracies in grating position, coupled with multi-harmonic fringes, lead to remnant oscillations and phase wraparound artifacts. We have developed an image recovery algorithm that uses additional harmonics, direct relative phase fitting, and phase step corrections to prevent them. The direct relative phase fitting removes the phase wraparound artifact. Correcting the phase step positions and introducing the additional harmonic removes the grating remnant artifact present in the transmission, differential-phase, and dark-field images. By modifying existing algorithms, the fit to the fringe pattern is greatly improved and artifacts are minimized, as we demonstrate with the imaging of several samples, including PMMA microspheres, ex vivo formalin fixed mouse lungs, and porous alumina.

physics.optics↗

arXiv2025

Analyzer-less X-ray Interferometry with Super-Resolution Methods

X-ray interferometry provides valuable information in terms of attenuation, small-angle scatter, and differential-phase contrast. This multi-modal contrast can aid in many clinical applications, such as lung diseases and breast cancer. However, standard interferometry has an analyzer grating that can increase the dose requirement to maintain the same image quality as a standard X-ray. We propose the use of super-resolution methods for X-ray grating interferometry without an analyzer, with detectors that fail to meet the Nyquist sampling rate needed for traditional image recovery algorithms. Detector phase steps are used to nominally recover the fringe sampling, followed by iterative recovery of the visibility and object parameters. This method enables Talbot-Lau interferometry without the X-ray absorbing analyzer. Removing the absorbing analyzer grating may improve dose efficiency and reduce system complexity. We demonstrate the use of super-resolution methods to iteratively reconstruct attenuation, differential-phase, and dark-field images using simulations of two-dimensional lung phantoms with lesions. A direct CdTe detector was simulated with pixel sizes of 55, 75, and 150 micron. The simulation results show that the proposed super-resolution iterative reconstruction method for Talbot-Lau Interferometry remains stable under the simulated noise conditions and can recover image parameters in cases where traditional algorithms cannot be used.

physics.optics↗

arXiv2024

X-ray Interferometry Using a Modulated Phase Grating: Theory and Experiments

X-ray grating interferometry allows for the simultaneous acquisition of attenuation, differential-phase contrast, and dark-field images, resulting from X-ray attenuation, refraction, and small-angle scattering, respectively. The modulated phase grating (MPG) interferometer is a recently developed grating interferometry system capable of generating a directly resolvable interference pattern using a relatively large period grating envelope function that is sampled at a pitch that allows for X-ray spatial coherence using a microfocus X-ray source or by use of a source G0 grating that follows the Lau condition. We present the theory of the MPG interferometry system for a 2-dimensional staggered grating, derived using Fourier optics, and we compare the theoretical predictions with experiments we have performed with a microfocus X-ray system at Pennington Biomedical Research Center, LSU. The theoretical and experimental fringe visibility is evaluated as a function of grating-to-detector distance. Quantitative experiments are performed with porous carbon and alumina samples, and qualitative analysis of attenuation and dark-field images of a dried anchovy are shown.

physics.optics↗

arXiv2023

Maximum-Likelihood Estimation of Glandular Fraction for Mammography and its Effect on Microcalcification Detection

Objective: Breast tissue is mainly a mixture of adipose and fibro-glandular tissue. Cancer risk and risk of undetected breast cancer increases with the amount of glandular tissue in the breast. Therefore, radiologists must report the total volume glandular fraction or a BI-RADS classification in screening and diagnostic mammography. A Maximum Likelihood algorithm is shown to estimate the pixel-wise glandular fraction from mammographic images. The pixel-wise glandular fraction provides information that helps localize dense tissue. The total volume glandular fraction can be calculated from pixel-wise glandular fraction. The algorithm was implemented for images acquired with an anti-scatter grid, and without using the anti-scatter grid but followed by software scatter removal. The work also studied if presenting the pixel-wise glandular fraction image alongside the usual mammographic image has the potential to improve the contrast-to-noise ratio on micro-calcifications in the breast. Results: For the TOPAS simulated images, the glandular fraction was estimated with a root mean squared error of 3.2% and 2.5% for the without and with anti-scatter grid cases. Average absolute errors were (3.7 +/- 2.4)% and (3.6 +/- 0.9)%, respectively. Results from DICOM clinical images (where the true glandular fraction is unknown) show that the algorithm gives a glandular fraction within the average range expected from the literature. For microcalcification detection, the contrast-to-noise ratio improved by 17.5-548% in DICOM images and 5.1-88% in TOPAS images. Conclusion: We show a method of accurate estimation of pixel-wise glandular fraction image, providing localization information of breast density. The glandular fraction images also showed an improvement in contrast to noise ratio for detecting microcalcifications, a risk factor in breast cancer.

physics.med-ph↗