Image enhancement in positron emission mammography

Nikolai V. Slavine; Stephen Seiler; Roderick W. McColl; Robert E. Lenkinski

doi:10.1117/12.2248758

24 February 2017 Image enhancement in positron emission mammography

Nikolai V. Slavine, Stephen Seiler, Roderick W. McColl, Robert E. Lenkinski

Proceedings Volume 10133, Medical Imaging 2017: Image Processing; 101331J (2017) https://doi.org/10.1117/12.2248758
Event: SPIE Medical Imaging, 2017, Orlando, Florida, United States

Abstract

Purpose: To evaluate an efficient iterative deconvolution method (RSEMD) for improving the quantitative accuracy of previously reconstructed breast images by commercial positron emission mammography (PEM) scanner. Materials and Methods: The RSEMD method was tested on breast phantom data and clinical PEM imaging data. Data acquisition was performed on a commercial Naviscan Flex Solo II PEM camera. This method was applied to patient breast images previously reconstructed with Naviscan software (MLEM) to determine improvements in resolution, signal to noise ratio (SNR) and contrast to noise ratio (CNR.) Results: In all of the patients’ breast studies the post-processed images proved to have higher resolution and lower noise as compared with images reconstructed by conventional methods. In general, the values of SNR reached a plateau at around 6 iterations with an improvement factor of about 2 for post-processed Flex Solo II PEM images. Improvements in image resolution after the application of RSEMD have also been demonstrated. Conclusions: A rapidly converging, iterative deconvolution algorithm with a novel resolution subsets-based approach RSEMD that operates on patient DICOM images has been used for quantitative improvement in breast imaging. The RSEMD method can be applied to clinical PEM images to improve image quality to diagnostically acceptable levels and will be crucial in order to facilitate diagnosis of tumor progression at the earliest stages. The RSEMD method can be considered as an extended Richardson-Lucy algorithm with multiple resolution levels (resolution subsets).

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Nikolai V. Slavine, Stephen Seiler, Roderick W. McColl, and Robert E. Lenkinski "Image enhancement in positron emission mammography", Proc. SPIE 10133, Medical Imaging 2017: Image Processing, 101331J (24 February 2017); https://doi.org/10.1117/12.2248758

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KEYWORDS

Image resolution

Image enhancement

Signal to noise ratio

Breast

Image quality

Reconstruction algorithms

Image restoration

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