| 1. |
- Costa, Arthur C., et al.
(författare)
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Assessment of projection interpolation to compensate for the increased radiation dose in DBTMI
- 2023
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Ingår i: Medical Imaging 2023 : Physics of Medical Imaging - Physics of Medical Imaging. - 1605-7422. - 9781510660311 ; 12463
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Konferensbidrag (refereegranskat)abstract
- The combination of digital breast tomosynthesis (DBT) with other imaging modalities has been investigated in order to improve the detection and diagnosis of breast cancer. Mechanical Imaging (MI) measures the stress over the surface of the compressed breast, using a pressure sensor, during radiographic examination and its response has shown a correlation with the presence of malignant lesions. Thus, the combination of DBT and MI (DBTMI) has shown potential to reduce false positive results in breast cancer screening. However, compared to the conventional DBT exam, the presence of the MI sensor during mammographic image acquisition may cause a slight increase in the radiation dose. This work presents a proposal to reduce the radiation dose in DBTMI exams by removing some projections from the original set and replacing them with synthetic projections generated by a video frame interpolation (VFI) neural network. We compared several DBTMI acquisition arrangements, considering the removal of 16% of the original projections, using a deformable physical breast phantom, and evaluated the quality of the reconstructed images based on the Normalized Root Mean Squared Error (NRMSE). The results showed that, for some arrangements, the slices reconstructed with the addition of synthetic DBTMI projections presented better quality than when they were reconstructed with the reduced set of projections. Further studies must be carried out to optimize the interpolation approach.
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| 2. |
- Tomic, Hanna, et al.
(författare)
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Simulation of breast lesions based upon fractal Perlin noise
- 2023
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Ingår i: Physica Medica. - 1120-1797. ; 114
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Steadily increasing use of computational/virtual phantoms in medical physics has motivated expanding development of new simulation methods and data representations for modelling human anatomy. This has emphasized the need for increased realism, user control, and availability. In breast cancer research, virtual phantoms have gained an important role in evaluating and optimizing imaging systems. For this paper, we have developed an algorithm to model breast abnormalities based on fractal Perlin noise. We demonstrate and characterize the extension of this approach to simulate breast lesions of various sizes, shapes, and complexity. Materials and method: Recently, we developed an algorithm for simulating the 3D arrangement of breast anatomy based on Perlin noise. In this paper, we have expanded the method to also model soft tissue breast lesions. We simulated lesions within the size range of clinically representative breast lesions (masses, 5–20 mm in size). Simulated lesions were blended into simulated breast tissue backgrounds and visualized as virtual digital mammography images. The lesions were evaluated by observers following the BI-RADS assessment criteria. Results: Observers categorized the lesions as round, oval or irregular, with circumscribed, microlobulated, indistinct or obscured margins. The majority of the simulated lesions were considered by the observers to have a realism score of moderate to well. The simulation method provides almost real-time lesion generation (average time and standard deviation: 1.4 ± 1.0 s). Conclusion: We presented a novel algorithm for computer simulation of breast lesions using Perlin noise. The algorithm enables efficient simulation of lesions, with different sizes and appearances.
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