Prof. Marcelo A. C. Vieira Profile

Prof. Marcelo A. C. Vieira

Associate Professor at University of Sao Paulo

Area of Expertise:

Image Processing , Digital Mammography , Medical Imaging , Denoising , Image Restoration , magnetic resonance imaging

Profile Summary

Prof. Marcelo Vieira is Associate Professor at the Department of Electrical and Computer Engineering, Sao Carlos School of Engineering, University of Sao Paulo (Brazil). With 25 years of experience in signal processing research, he has specific training and expertise in developing image processing methods to enhance the quality of medical images. Prof. Vieira has been a leading investigator in numerous studies focusing on the assessment of clinical imaging systems and the development of image processing methods to improve image quality. He serves as the Director of the Laboratory of Computer Vision at the University of Sao Paulo. His research interests lie in the areas of image processing and artificial intelligence applied to clinical imaging, mainly in the following subjects: digital mammography, digital breast tomosynthesis, magnetic resonance imaging, image processing, image restoration, denoising, noise modeling, noise simulation for medical images, radiation dose reduction, artificial intelligence, machine learning, neural networks, deep learning and computer aided diagnosis (CAD) systems.

Publications (34)

Proceedings Article | 7 April 2023 Poster + Paper

Poster + Paper

Assessment of projection interpolation to compensate for the increased radiation dose in DBTMI

Arthur Costa, Anna Bjerkén, Magnus Dustler, Anders Tingberg, Predrag Bakic, Marcelo A. Vieira

Proceedings Volume 12463, 1246344 (2023) https://doi.org/10.1117/12.2655006

KEYWORDS: Breast cancer, Interpolation, Digital breast tomosynthesis, Breast, Sensors, Image sensors, Visualization, Neural networks, Image quality

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Proceedings Article | 7 April 2023 Poster + Paper

Poster + Paper

Computational method to artificially insert clusters of microcalcifications in digital breast tomosynthesis

Rodrigo Vimieiro, Lucas Borges, Bruno Barufaldi, Andrew D. Maidment, Renato Caron, Silvia M. P. Sabino, Ge Wang, Marcelo A. Vieira

Proceedings Volume 12463, 124632N (2023) https://doi.org/10.1117/12.2653857

KEYWORDS: Digital breast tomosynthesis, Medical imaging, Computer simulations, Modulation transfer functions, Breast cancer, Voxels, Image processing, Cancer detection, Breast

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Proceedings Article | 3 April 2023 Poster + Paper

Poster + Paper

Assessing the impact of correlated noise in digital mammography: a virtual clinical trial

Lucas Soares, Renann Brandao, Lucas Borges, Renato Caron, Bruno Barufaldi, Andrew D. Maidment, Marcelo A. Vieira

Proceedings Volume 12467, 1246714 (2023) https://doi.org/10.1117/12.2654111

KEYWORDS: Image quality, Digital mammography, Quantum noise, Clinical trials, Image processing, Medical imaging

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Proceedings Article | 13 July 2022 Paper

Paper

Imposing noise correlation fidelity on digital breast tomosynthesis restoration through deep learning techniques

Rodrigo Vimieiro, Lucas Borges, Ge Wang, Marcelo A. C. Vieira

Proceedings Volume 12286, 122861C (2022) https://doi.org/10.1117/12.2626634

KEYWORDS: Picosecond phenomena, Digital breast tomosynthesis, Image restoration, Breast, Visualization, Breast cancer, Neural networks, Image quality, Denoising, Zoom lenses

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Proceedings Article | 13 July 2022 Paper

Paper

Denoising of mammograms subject to structural and spatially-correlated noise: a virtual clinical trial

Lucas Borges, Marco Brochi, Marcelo A. C. Vieira, Paulo de Azevedo-Marques

Proceedings Volume 12286, 1228606 (2022) https://doi.org/10.1117/12.2626629

KEYWORDS: Denoising, Mammography, Interference (communication), Image quality, Image processing, Signal processing, Clinical trials, Chromium, Zoom lenses, Picosecond phenomena

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Proceedings Article | 13 July 2022 Paper

Paper

Assessment of video frame interpolation network to generate digital breast tomosynthesis projections

Arthur Costa, Rodrigo Vimieiro, Lucas Borges, Bruno Barufaldi, Andrew D. A. Maidment, Marcelo A. C. Vieira

Proceedings Volume 12286, 122861D (2022) https://doi.org/10.1117/12.2625748

KEYWORDS: Digital breast tomosynthesis, Image quality, Video, Breast, Visualization, Neural networks, Reconstruction algorithms, Signal to noise ratio, Medical imaging, Image analysis

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Proceedings Article | 13 July 2022 Paper

Paper

Using virtual clinical trials to assess objective image quality metrics in the task of microcalcification localization in digital mammography

Lucas Soares, Lucas Borges, Bruno Barufaldi, Andrew D. A. Maidment, Marcelo A. C. Vieira

Proceedings Volume 12286, 1228603 (2022) https://doi.org/10.1117/12.2625745

KEYWORDS: Image quality, Image processing, Digital mammography, Signal to noise ratio, Mammography, Image analysis, Distortion, Clinical trials, Medical imaging, Image quality standards

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Proceedings Article | 13 July 2022 Paper

Paper

Suppressing noise correlation in digital breast tomosynthesis using convolutional neural network and virtual clinical trials

Rodrigo Vimieiro, Lucas Borges, Renato Caron, Bruno Barufaldi, Andrew D. A. Maidment, Ge Wang, Marcelo A. C. Vieira

Proceedings Volume 12286, 122861B (2022) https://doi.org/10.1117/12.2625357

KEYWORDS: Digital breast tomosynthesis, Picosecond phenomena, Image restoration, Quantum electronics, Denoising, Convolutional neural networks, Clinical trials, Sensors, Computer simulations, Breast

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Proceedings Article | 4 April 2022 Poster + Presentation + Paper

Poster + Presentation + Paper

Assessment of training strategies for convolutional neural network to restore low-dose digital breast tomosynthesis projections

Rodrigo de Barros Vimieiro, Lucas Rodrigues Borges, Bruno Barufaldi, Andrew Maidment, Ge Wang, Marcelo Andrade da Costa Vieira

Proceedings Volume 12031, 120311V (2022) https://doi.org/10.1117/12.2609945

KEYWORDS: Digital breast tomosynthesis, Breast, Signal to noise ratio, Image restoration, Denoising, Network architectures

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Proceedings Article | 15 February 2021 Poster + Presentation + Paper

Poster + Presentation + Paper

Iterative method to achieve noise variance stabilization in single raw digital breast tomosynthesis

Renann Brandão, Lucas Borges, Bruno Barufaldi, Trevor Vent, Renato Caron, Bruno Oliveira, Andrew D. Maidment, Marcelo A. Vieira

Proceedings Volume 11595, 115954R (2021) https://doi.org/10.1117/12.2580965

KEYWORDS: Iterative methods, Interference (communication), Digital breast tomosynthesis, Calibration, Systems modeling, Denoising, X-rays, Transform theory, Data analysis

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Proceedings Article | 22 May 2020 Paper

Paper

Transfer learning in deep convolutional neural networks for detection of architectural distortion in digital mammography

Arthur Costa, Helder C. Oliveira, Lucas Borges, Marcelo A. Vieira

Proceedings Volume 11513, 115130N (2020) https://doi.org/10.1117/12.2564348

KEYWORDS: Mammography, Digital mammography, Data modeling, Convolutional neural networks, Architectural distortion, Databases, Network architectures, Computer aided diagnosis and therapy, Breast, Visualization

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Proceedings Article | 22 May 2020 Paper

Paper

Effect of denoising on the localization of microcalcification clusters in digital mammography

Lucas Borges, Renato Caron, Paulo Azevedo-Marques, Marcelo A. Vieira

Proceedings Volume 11513, 115130K (2020) https://doi.org/10.1117/12.2564316

KEYWORDS: Denoising, Image processing, Digital mammography, Mammography, Image quality, Signal to noise ratio, Cancer, Breast imaging, Signal processing, Interference (communication)

Read Abstract +

Proceedings Article | 13 March 2019 Paper

Paper

Exploratory learning with convolutional autoencoder for discrimination of architectural distortion in digital mammography

Helder C. de Oliveira, Carlos F. Melo, Juliana Catani, Nestor de Barros, Marcelo da Costa Vieira

Proceedings Volume 10950, 109502F (2019) https://doi.org/10.1117/12.2513021

KEYWORDS: Digital mammography, Mammography, Architectural distortion, Data modeling, Breast cancer, Computer aided diagnosis and therapy, Breast, Computer-aided diagnosis, Digital imaging

Read Abstract +

Proceedings Article | 4 March 2019 Presentation + Paper

Presentation + Paper

A 2-AFC study to validate artificially inserted microcalcification clusters in digital mammography

Lucas Borges, Paulo de Azevedo Marques, Marcelo A. Vieira

Proceedings Volume 10952, 109520R (2019) https://doi.org/10.1117/12.2513031

KEYWORDS: Mammography, Breast, Digital mammography, Cancer, Image processing, Breast cancer, Tissues, Visualization, Surface plasmons

Read Abstract +

Proceedings Article | 1 March 2019 Presentation + Paper

Presentation + Paper

Noise measurements from reconstructed digital breast tomosynthesis

Rodrigo Vimieiro, Lucas Borges, Renato Caron, Bruno Barufaldi, Predrag Bakic, Andrew D. Maidment, Marcelo A. Vieira

Proceedings Volume 10948, 109480C (2019) https://doi.org/10.1117/12.2512977

KEYWORDS: Digital breast tomosynthesis, Signal to noise ratio, Sensors, Reconstruction algorithms, Image processing, Breast, X-rays, Systems modeling, X-ray detectors, Fluctuations and noise

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Proceedings Article | 1 March 2019 Paper

Paper

Bayesian reconstruction for digital breast tomosynthesis using a non-local Gaussian Markov random field a priori model

Denis Salvadeo, Rodrigo Vimieiro, Marcelo A. Vieira, Andrew D. Maidment

Proceedings Volume 10948, 109485C (2019) https://doi.org/10.1117/12.2513140

KEYWORDS: Digital breast tomosynthesis, Reconstruction algorithms, Inverse problems, Breast, Tomography, Denoising, Imaging systems

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Proceedings Article | 1 March 2019 Paper

Paper

Analysis of feature relevance using an image quality index applied to digital mammography

Arthur Costa, Bruno Barufaldi, Lucas Borges, Michael Biehl, Andrew D. Maidment, Marcelo A. Vieira

Proceedings Volume 10948, 109485R (2019) https://doi.org/10.1117/12.2512975

KEYWORDS: Image quality, Breast, Digital mammography, Quantization, Mammography, Prototyping, Automatic exposure, Automatic control, Digital imaging, Calibration

Read Abstract +

Proceedings Article | 9 March 2018 Paper

Paper

Application of neural networks to model the signal-dependent noise of a digital breast tomosynthesis unit

Fabrício Brito, Lucas Borges, Igor Guerrero, Predrag Bakic, Andrew D. Maidment, Marcelo A. Vieira

Proceedings Volume 10573, 105730J (2018) https://doi.org/10.1117/12.2293659

KEYWORDS: Digital breast tomosynthesis, Calibration, Interference (communication), Chest, Data modeling, Artificial neural networks, Neural networks, Sensors, Signal processing, Imaging systems

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Proceedings Article | 7 March 2018 Presentation + Paper

Presentation + Paper

Restored low-dose digital breast tomosynthesis: a perception study

Lucas Borges, Predrag Bakic, Andrew D. Maidment, Marcelo A. Vieira

Proceedings Volume 10577, 1057705 (2018) https://doi.org/10.1117/12.2293252

KEYWORDS: Digital breast tomosynthesis, Signal to noise ratio, Denoising, Image quality, Calibration, Image processing, Breast, Interference (communication), Signal processing, Computer simulations

Read Abstract +

Proceedings Article | 27 February 2018 Paper

Paper

Reduction of false-positives in a CAD scheme for automated detection of architectural distortion in digital mammography

Helder C. de Oliveira, Arianna Mencattini, Paola Casti, Eugenio Martinelli, Corrado di Natale, Juliana Catani, Nestor de Barros, Carlos F. E. Melo, Adilson Gonzaga, Marcelo A. Vieira

Proceedings Volume 10575, 105752P (2018) https://doi.org/10.1117/12.2293388

KEYWORDS: Image segmentation, Architectural distortion, Computer aided diagnosis and therapy, Volume rendering, Digital mammography, Mammography, Breast, Computing systems, Statistical analysis, Binary data

Read Abstract +

Proceedings Article | 10 March 2017 Paper

Paper

Assessment of automatic exposure control performance in digital mammography using a no-reference anisotropic quality index

Bruno Barufaldi, Lucas Borges, Predrag Bakic, Marcelo A. C. Vieira, Homero Schiabel, Andrew D. Maidment

Proceedings Volume 10136, 101360U (2017) https://doi.org/10.1117/12.2255629

KEYWORDS: Image quality, Breast, Automatic exposure, Automatic control, Mammography, Digital mammography, Anisotropy, Image processing, Skin, Image compression, Binary data

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Proceedings Article | 9 March 2017 Presentation + Paper

Presentation + Paper

Metal artifact reduction using a patch-based reconstruction for digital breast tomosynthesis

Lucas Borges, Predrag Bakic, Andrew D. Maidment, Marcelo A. Vieira

Proceedings Volume 10132, 1013221 (2017) https://doi.org/10.1117/12.2254138

KEYWORDS: Digital breast tomosynthesis, Signal to noise ratio, Metals, Breast, Interference (communication), Breast cancer, Tomography, Denoising, Reconstruction algorithms, Visualization

Read Abstract +

Proceedings Article | 9 March 2017 Presentation + Paper

Presentation + Paper

Pipeline for effective denoising of digital mammography and digital breast tomosynthesis

Lucas Borges, Predrag Bakic, Alessandro Foi, Andrew D. Maidment, Marcelo A. Vieira

Proceedings Volume 10132, 1013206 (2017) https://doi.org/10.1117/12.2255058

KEYWORDS: Denoising, Digital mammography, Calibration, Sensors, Interference (communication), Image filtering, Digital breast tomosynthesis, Modulation transfer functions, Signal to noise ratio, Breast

Read Abstract +

Proceedings Article | 3 March 2017 Paper

Paper

A new texture descriptor based on local micro-pattern for detection of architectural distortion in mammographic images

Helder C. de Oliveira, Diego Moraes, Gustavo Reche, Lucas Borges, Juliana Catani, Nestor de Barros, Carlos F. Melo, Adilson Gonzaga, Marcelo A. Vieira

Proceedings Volume 10134, 101342U (2017) https://doi.org/10.1117/12.2255516

KEYWORDS: Architectural distortion, Mammography, Feature extraction, Breast, Computing systems, Image classification, Computer-aided diagnosis, Machine vision, Computer vision technology, Breast cancer, Tissues, Neurons, Digital mammography, Binary data, Neural networks

Read Abstract +

Proceedings Article | 24 March 2016 Paper

Paper

Validation of no-reference image quality index for the assessment of digital mammographic images

Helder C. de Oliveira, Bruno Barufaldi, Lucas Borges, Salvador Gabarda, Predrag Bakic, Andrew D. Maidment, Homero Schiabel, Marcelo A. Vieira

Proceedings Volume 9787, 978713 (2016) https://doi.org/10.1117/12.2217229

KEYWORDS: Image quality, Digital imaging, Digital mammography, Mammography, Spatial resolution, Visual system, Breast, Signal to noise ratio, Image quality standards, Image analysis, Software development

Read Abstract +

To ensure optimal clinical performance of digital mammography, it is necessary to obtain images with high spatial resolution and low noise, keeping radiation exposure as low as possible. These requirements directly affect the interpretation of radiologists. The quality of a digital image should be assessed using objective measurements. In general, these methods measure the similarity between a degraded image and an ideal image without degradation (ground-truth), used as a reference. These methods are called Full-Reference Image Quality Assessment (FR-IQA). However, for digital mammography, an image without degradation is not available in clinical practice; thus, an objective method to assess the quality of mammograms must be performed without reference. The purpose of this study is to present a Normalized Anisotropic Quality Index (NAQI), based on the Rényi entropy in the pseudo-Wigner domain, to assess mammography images in terms of spatial resolution and noise without any reference. The method was validated using synthetic images acquired through an anthropomorphic breast software phantom, and the clinical exposures on anthropomorphic breast physical phantoms and patient’s mammograms. The results reported by this noreference index follow the same behavior as other well-established full-reference metrics, e.g., the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). Reductions of 50% on the radiation dose in phantom images were translated as a decrease of 4dB on the PSNR, 25% on the SSIM and 33% on the NAQI, evidencing that the proposed metric is sensitive to the noise resulted from dose reduction. The clinical results showed that images reduced to 53% and 30% of the standard radiation dose reported reductions of 15% and 25% on the NAQI, respectively. Thus, this index may be used in clinical practice as an image quality indicator to improve the quality assurance programs in mammography; hence, the proposed method reduces the subjectivity inter-observers in the reporting of image quality assessment.

Proceedings Article | 18 March 2015 Paper

Paper

Feasibility study of dose reduction in digital breast tomosynthesis using non-local denoising algorithms

Marcelo A. Vieira, Helder C. de Oliveira, Polyana Nunes, Lucas Borges, Predrag Bakic, Bruno Barufaldi, Raymond Acciavatti, Andrew D. Maidment

Proceedings Volume 9412, 94122C (2015) https://doi.org/10.1117/12.2082398

KEYWORDS: Digital breast tomosynthesis, Denoising, Image quality, Image quality standards, Reconstruction algorithms, Optical filters, Breast, Image filtering, Tomography, Signal to noise ratio

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Proceedings Article | 18 March 2015 Paper

Paper

Method for inserting noise in digital mammography to simulate reduction in radiation dose

Lucas Borges, Helder C. de Oliveira, Polyana Nunes, Marcelo A. Vieira

Proceedings Volume 9412, 94125J (2015) https://doi.org/10.1117/12.2082257

KEYWORDS: Mammography, Interference (communication), Digital mammography, Sensors, Modulation transfer functions, Computer simulations, X-rays, Error analysis, Electroluminescence, X-ray imaging

Read Abstract +

Proceedings Article | 19 March 2013 Paper

Paper

Effect of denoising on the quality of reconstructed images in digital breast tomosynthesis

Marcelo Vieira, Predrag Bakic, Andrew Maidment

Proceedings Volume 8668, 86680C (2013) https://doi.org/10.1117/12.2007804

KEYWORDS: Denoising, Digital breast tomosynthesis, Filtering (signal processing), Image quality, Interference (communication), Breast, Reconstruction algorithms, 3D modeling, Tomography, Image filtering

Read Abstract +

Proceedings Article | 4 March 2009 Paper

Paper

Preprocessing for improving CAD scheme performance for microcalcification detection based on mammography imaging quality parameters

Homero Schiabel, Marcelo A. C. Vieira, Liliane Ventura

Proceedings Volume 7260, 72602G (2009) https://doi.org/10.1117/12.812015

KEYWORDS: Mammography, Image processing, Computer aided diagnosis and therapy, Breast, Optical transfer functions, Databases, Image quality, Computer aided design, Digital mammography, Image segmentation

Read Abstract +

Proceedings Article | 18 March 2008 Paper

Paper

Computational method for automatic determination of radiographic equipment anode angle

Marcelo A. Vieira, Paulo de Oliveira, Homero Schiabel

Proceedings Volume 6913, 69133M (2008) https://doi.org/10.1117/12.770942

KEYWORDS: X-rays, Point spread functions, Algorithm development, Image processing, X-ray imaging, Manufacturing, Image quality, Lead, Image analysis, Image filtering

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Proceedings Article | 6 May 2004 Paper

Paper

Evaluation of film digitizer's spatial resolution by slit image computational analysis

Mauricio Escarpinati, Marcelo Vieira, Homero Schiabel

Proceedings Volume 5368, (2004) https://doi.org/10.1117/12.536056

KEYWORDS: Modulation transfer functions, Spatial resolution, Digital imaging, Image analysis, Optical scanning, Medical imaging, Image processing, Microscopes, Image resolution, Analog electronics

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Proceedings Article | 6 May 2004 Paper

Paper

Choosing proper mammography screen-film system by computer simulation

Kathy Senhorini, Homero Schiabel, Marcelo Vieira, Mauricio Escarpinati

Proceedings Volume 5368, (2004) https://doi.org/10.1117/12.534184

KEYWORDS: Mammography, Absorbance, Computer simulations, Image quality, Fiber optic gyroscopes, X-rays, Computing systems, Image acquisition, Data modeling, X-ray imaging

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Proceedings Article | 5 June 2003 Paper

Paper

Use of a film scanner as a microdensitometer for optical transfer function and focal spot measurements

Marcelo Vieira, Homero Schiabel, Mauricio Escarpinati

Proceedings Volume 5030, (2003) https://doi.org/10.1117/12.480228

KEYWORDS: Optical transfer functions, Modulation transfer functions, Scanners, X-rays, Absorbance, Phase transfer function, Mammography, Image processing, X-ray imaging, Spatial frequencies

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Proceedings Article | 7 June 2001 Paper

Paper

In-vitro corneal transparency measuring system

Liliane Ventura, Marcelo da Costa Vieira, Flavio Isaac, Caio Chiaradia, Sidney Faria de Sousa

Proceedings Volume 4245, (2001) https://doi.org/10.1117/12.429281

KEYWORDS: Cornea, Transparency, Tissues, Sensors, Eye, In vitro testing, Tissue optics, Lamps, Imaging systems, Electronic circuits

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Showing 5 of 34 publications

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