Simulation of breast lesions based upon fractal Perlin noise
(2023) In Physica Medica 114.- 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... (More)
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.
(Less)
- author
- Tomic, Hanna LU ; Costa, Arthur C. ; Bjerkén, Anna LU ; Vieira, Marcelo A.C. ; Zackrisson, Sophia LU ; Tingberg, Anders LU ; Timberg, Pontus LU ; Dustler, Magnus LU and Bakic, Predrag R. LU
- organization
- publishing date
- 2023-10
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Computational phantoms, Lesion simulation, Mammography, Virtual clinical trials
- in
- Physica Medica
- volume
- 114
- article number
- 102681
- publisher
- ISTITUTI EDITORIALI E POLGRAFICI INTERNAZIONALI
- external identifiers
-
- pmid:37748358
- scopus:85172381986
- ISSN
- 1120-1797
- DOI
- 10.1016/j.ejmp.2023.102681
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2023 Associazione Italiana di Fisica Medica e Sanitaria
- id
- 2e60e752-48cf-4a3c-b7c1-f8566c137c87
- date added to LUP
- 2024-01-12 10:18:20
- date last changed
- 2024-04-27 05:43:46
@article{2e60e752-48cf-4a3c-b7c1-f8566c137c87, abstract = {{<p>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.</p>}}, author = {{Tomic, Hanna and Costa, Arthur C. and Bjerkén, Anna and Vieira, Marcelo A.C. and Zackrisson, Sophia and Tingberg, Anders and Timberg, Pontus and Dustler, Magnus and Bakic, Predrag R.}}, issn = {{1120-1797}}, keywords = {{Computational phantoms; Lesion simulation; Mammography; Virtual clinical trials}}, language = {{eng}}, publisher = {{ISTITUTI EDITORIALI E POLGRAFICI INTERNAZIONALI}}, series = {{Physica Medica}}, title = {{Simulation of breast lesions based upon fractal Perlin noise}}, url = {{http://dx.doi.org/10.1016/j.ejmp.2023.102681}}, doi = {{10.1016/j.ejmp.2023.102681}}, volume = {{114}}, year = {{2023}}, }