Data from: Scatter correction for contrast-enhanced digital breast tomosynthesis with a dual-layer detector
Data files
Mar 05, 2025 version files 16.20 GB
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README.md
3.43 KB
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Related_Codes.7z
2.75 KB
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Simulated_Data.7z
16.20 GB
Abstract
Purpose: Contrast-enhanced digital breast tomosynthesis (CEDBT) highlights breast tumors with neo-angiogenesis. A recently proposed CEDBT system with a dual-layer (DL) flat-panel-detector enables simultaneous acquisition of high-energy (HE) and low-energy (LE) projection images with a single exposure, which reduces acquisition time and eliminates motion artifacts. However, x-ray scatter degrades image quality and lesion detectability. In this work, we propose a practical method for accurate and robust scatter correction (SC) for DL-CEDBT.
Approach: The proposed hybrid SC method combines the advantages of a two-kernel iterative convolution method and an empirical interpolation strategy, which accounts for the reduced scatter from the peripheral breast region due to thickness roll-off and the scatter contribution from the region outside the breast. Scatter point spread functions were generated using Monte Carlo simulations with different breast glandular fractions, compressed thicknesses, and projection angles. Projection images and ground truth scatter maps of anthropomorphic digital breast phantoms were simulated to evaluate the performance of the proposed SC method and three other kernel- and interpolation-based methods. The mean absolute relative error (MARE) between scatter estimates and ground truth was used as the metric for SC accuracy.
Results: DL-CEDBT shows scatter characteristics different from dual-shot (DS), primarily due to the two energy peaks of the incident spectrum and the structure of the DL detector. Compared to the other methods investigated, the proposed hybrid SC method showed superior accuracy and robustness, with MARE of approximately 3.1% for all LE and HE projection images of different phantoms in both CC and MLO views. After SC, cupping artifacts in the dual-energy image were removed, and the signal difference-to-noise ratio was improved by 82.0% for 8 mm iodine objects.
Conclusions: A practical SC method was developed, which provided accurate and robust scatter estimates to improve image quality and lesion detectability for DL-CEDBT.
[https://doi.org/10.1117/1.JMI.12.S1.S13008)
Folders and Files
Folder: Simulated_Data
Description: Contains simulated data used in the study, including scatter point spread function (sPSF) kernels, anthropomorphic digital breast phantoms, and projection images. Details on the simulation tool and imaging geometry are available in the manuscript.
Folder: Simulated_Data\ScatterPSF_Kernels
Description: Simulated sPSF kernels for the front and back layer detectors.
Folder: Simulated_Data\ScatterPSF_Kernels\front\50gld_40mm
Description: sPSF kernels of the front layer for a 40 mm thick compressed breast with a 50% glandular fraction
Description: front layer sPSF kernels at -8 degree oblique projection angle, stored at 680 µm x 680 µm spatial resolution in Matlab array format, convertible to CSV.
Folder: Simulated_Data\Projection_Images
Description: Simulated projection images of seven anthropomorphic breast phantoms, used to validate the hybrid scatter correction method.
Folder: Simulated_Data\Projection_Images\pc_1_4.16cmMLO_3.74cmCC
Description: Simulated projection images of the first breast phantom which has thicknesses of 4.16 cm and 3.74 cm in mediolateral oblique (MLO) and craniocaudal (CC) views, respectively.
Description: front layer projection images of first breast phantom compressed in CC view.
Description: front projection image at (XX-1)x2.0833-25 degree oblique angle for the first breast phantom in CC. The image has dimension of 3584x1504x2 and datatype of 'float'. The first channel is scatter-present image, while the second is scatter-absent image. Files in Raw format can be opened using imageJ or Matlab.
Instruction: When use ImageJ to open the .raw file, follow these steps:
1) Click 'File' in the top menu bar.
2) Select 'Import' and then choose 'Raw'.
3) Pick the .raw image you wish to open. Here, an image with dimensions of 3584x1504x2 and a datatype of 'float' is used as an example.
4) Set the following parameters:
- 'Image Type': 32-bit Real
- 'Width': 3584
- 'Height': 1504
- 'Offset to first image': 0
- 'Number of images': 2
- 'Gap between images': 0
- 'White is zero': Uncheck
- 'Little-endian byte order': Check
- 'Open all files in folder': Uncheck
- 'Use virtual stack': Uncheck
5) Click 'OK' to proceed.
Folder: Related_Codes
Description: Includes two Matlab functions for the hybrid scatter correction method.
File: Related_Codes\iter_scatcorr_simul_XW.m
Description: Function code for the two-kernel iterative convolution strategy (variables explained in code).
File: Related_Codes\fit_scatcorr_simul_XW.m
Description: Function code for the interpolation strategy to estimate scatter in the periphereal region.
Access information
For additional data requests related to the work, please refer to the contact information in the associated manuscript.