Optimization of 2D image reconstruction for positron emission mammography using IDL. - Nuno Oliveira 003; Nuno Matela; R. Bugalho; Nuno C. Ferreira; Pedro Almeida 001 (Comput. Biol. Medicine, 2009)

Choosing the ART relaxation parameter for Clear-PEM 2D image reconstruction. - J. Mesquita; Nuno Matela; Nuno Oliveira 003; Mónica V. Martins; Pedro Almeida 001 (Comput. Methods Programs Biomed., 2010)

3D Total Variation Minimization Filter for Breast Tomosynthesis Imaging. - Ana M. Mota; Nuno Oliveira 003; Pedro Almeida 001; Nuno Matela (Digital Mammography / IWDM, 2016)

Dynamic relaxation in algebraic reconstruction technique (ART) for breast tomosynthesis imaging. - Nuno Oliveira 003; Ana M. Mota; Nuno Matela; L. Janeiro; Pedro Almeida 001 (Comput. Methods Programs Biomed., 2016)

VRRRRoom: Virtual Reality for Radiologists in the Reading Room. - Maurício Sousa; Daniel Mendes; Soraia Paulo; Nuno Matela; Joaquim A. Jorge; Daniel Simões Lopes (CHI, 2017)

Demo hour. - Paden Shorey; Audrey Girouard; Sang Ho Yoon; Yunbo Zhang; Ke Huo; Karthik Ramani; Maurício Sousa; Daniel Mendes; Soraia Paulo; Nuno Matela; Joaquim A. Jorge; Daniel Simões Lopes; et al. (Interactions, 2017)

Digital Breast Tomosynthesis imaging using compressed sensing based reconstruction for 10 radiation doses real data. - Adem Polat; Nuno Matela; Ali Dinler; Yu Shrike Zhang; Isa Yildirim (Biomed. Signal Process. Control., 2019)

Impact of total variation minimization in volume rendering visualization of breast tomosynthesis data. - Ana M. Mota; Matthew J. Clarkson; Pedro Almeida 001; Luis Peralta; Nuno Matela (Comput. Methods Programs Biomed., 2020)

Optimization of Breast Tomosynthesis Visualization through 3D Volume Rendering. - Ana M. Mota; Matthew J. Clarkson; Pedro Almeida 001; Nuno Matela (J. Imaging, 2020)

An Enhanced Visualization of DBT Imaging Using Blind Deconvolution and Total Variation Minimization Regularization. - Ana M. Mota; Matthew J. Clarkson; Pedro Almeida 001; Nuno Matela (IEEE Trans. Medical Imaging, 2020)

Breast Cancer Risk Assessment: A Review on Mammography-Based Approaches. - João Mendes; Nuno Matela (J. Imaging, 2021)

Detection of Microcalcifications in Digital Breast Tomosynthesis using Faster R-CNN and 3D Volume Rendering. - Ana M. Mota; Matthew J. Clarkson; Pedro Almeida 001; Nuno Matela (BIOIMAGING, 2022)

AI in Breast Cancer Imaging: A Survey of Different Applications. - João Mendes; José Domingues; Helena Aidos; Nuno C. Garcia; Nuno Matela (J. Imaging, 2022)

Automatic Classification of Simulated Breast Tomosynthesis Whole Images for the Presence of Microcalcification Clusters Using Deep CNNs. - Ana M. Mota; Matthew J. Clarkson; Pedro Almeida 001; Nuno Matela (J. Imaging, 2022)

Digital Breast Tomosynthesis: Towards Dose Reduction through Image Quality Improvement. - Ana M. Mota; João Mendes; Nuno Matela (J. Imaging, 2023)

Make It Less Complex: Autoencoder for Speckle Noise Removal - Application to Breast and Lung Ultrasound. - Duarte Oliveira-Saraiva; João Mendes; João Leote; Filipe André Gonzalez; Nuno C. Garcia; Hugo Alexandre Ferreira; Nuno Matela (J. Imaging, 2023)

Lumbar intervertebral disc segmentation for computer modeling and simulation. - Rodrigo Matos; Paulo Rui Fernandes; Nuno Matela; Andre P. G. Castro (Comput. Methods Programs Biomed., 2023)

Decoding Breast Cancer: Using Radiomics to Non-Invasively Unveil Molecular Subtypes Directly from Mammographic Images. - Manon A. G. Bakker; Maria de Lurdes Ovalho; Nuno Matela; Ana M. Mota (J. Imaging, 2024)

You get the best of both worlds? Integrating deep learning and traditional machine learning for breast cancer risk prediction. - João Mendes; Bernardo Oliveira; Carolina Araújo; Joana Galrão; Nuno C. Garcia; Nuno Matela (Comput. Biol. Medicine, 2025)