Dose savings in digital breast tomosynthesis through image processing

• Ano de defesa: 2017
• Autor(a) principal: Borges, Lucas Rodrigues
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Breast tomosynthesis; Dose reduction; Image restoration; Injeção de ruído; Mammography; Mamografia digital; Mistura Poisson-Gaussiana; Noise injection; Noise suppression; Poisson noise; Poisson-Gaussian mixture; Redução de dose de radiação; Redução de ruído; Restauração de imagem; Ruído Poisson; Tomossíntese digital
• Link de acesso: http://www.teses.usp.br/teses/disponiveis/18/18152/tde-02082017-164211/

In x-ray imaging, the x-ray radiation must be the minimum necessary to achieve the required diagnostic objective, to ensure the patients safety. However, low-dose acquisitions yield images with low quality, which affect the radiologists image interpretation. Therefore, there is a compromise between image quality and radiation dose. This work proposes an image restoration framework capable of restoring low-dose acquisitions to achieve the quality of full-dose acquisitions. The contribution of the new method includes the capability of restoring images with quantum and electronic noise, pixel offset and variable detector gain. To validate the image processing chain, a simulation algorithm was proposed. The simulation generates low-dose DBT projections, starting from fulldose images. To investigate the feasibility of reducing the radiation dose in breast cancer screening programs, a simulated pre-clinical trial was conducted using the simulation and the image processing pipeline proposed in this work. Digital breast tomosynthesis (DBT) images from 72 patients were selected, and 5 human observers were invited for the experiment. The results suggested that a reduction of up to 30% in radiation dose could not be perceived by the human reader after the proposed image processing pipeline was applied. Thus, the image processing algorithm has the potential to decrease radiation levels in DBT, also decreasing the cancer induction risks associated with the exam.