Discrete Reconstruction Techniques. - Attila Kuba; László Ruskó; Zoltán Kiss; Antal Nagy (Electron. Notes Discret. Math., 2005)

Multi-resolution method for binary tomography. - László Ruskó; Attila Kuba (Electron. Notes Discret. Math., 2005)

Automatic segmentation of the liver from multi- and single-phase contrast-enhanced CT images. - László Ruskó; György Bekes; Márta Fidrich (Medical Image Anal., 2009)

Comparison and Evaluation of Methods for Liver Segmentation From CT Datasets. - Tobias Heimann; Bram van Ginneken; Martin Styner; Yulia Arzhaeva; Volker Aurich; Christian Bauer 001; Andreas Beck 001; Christoph Becker 002; Reinhard Beichel; György Bekes; Fernando Bello; Gerd Karl Binnig; et al. (IEEE Trans. Medical Imaging, 2009)

Liver fat quantification using fast kVp-switching dual energy CT. - András Kriston; Paulo R. S. Mendonça; Alvin C. Silva; Robert G. Paden; William Pavlicek; Dushyant Sahani; Benedek Janos Kis; László Ruskó; Darin Okerlund; Rahul Bhotika (Image Processing, 2011)

Liver segmentation for contrast-enhanced MR images using partitioned probabilistic model. - László Ruskó; György Bekes (Int. J. Comput. Assist. Radiol. Surg., 2011)

Virtual volume resection using multi-resolution triangular representation of B-spline surfaces. - László Ruskó; Ilona Mátéka; András Kriston (Comput. Methods Programs Biomed., 2013)

Automated Detection of Anatomical Regions in Magnetic Resonance Images. - Márton József Tóth; Tamas Blaskovics; László Ruskó; Gaspar Delso; Balázs Csébfalvi (VMV, 2014)

Automated liver lesion detection in CT images based on multi-level geometric features. - László Ruskó; Ádám Perényi (Int. J. Comput. Assist. Radiol. Surg., 2014)

Automated segmentation methods for liver analysis in oncology applications - László Ruskó (2014)

A Self-learning Tumor Segmentation Method on DCE-MRI Images. - Szabolcs Urbán; László Ruskó; Antal Nagy (ICIAR, 2016)

Automatic recognition of anatomical regions in three-dimensional medical images. - Márton József Tóth; László Ruskó; Balázs Csébfalvi (Comput. Biol. Medicine, 2016)

Automatic Recognition of Anatomical Regions in Computed Tomography Images. - Márton József Tóth; László Ruskó; Balázs Csébfalvi (Period. Polytech. Electr. Eng. Comput. Sci., 2018)

Deep-Learning-based Segmentation of Organs-at-Risk in the Head for MR-assisted Radiation Therapy Planning. - László Ruskó; Marta E. Capala; Vanda Czipczer; Bernadett Kolozsvári; Borbála Deák-Karancsi; Renáta Czabány; Bence Gyalai; Tao Tan; Zoltán Végváry; Emoke Borzasi; Zsófia Együd; Renáta Kószó; et al. (BIOIMAGING, 2021)

Pristine Annotations-Based Multi-modal Trained Artificial Intelligence Solution to Triage Chest X-Ray for COVID-19. - Tao Tan; Bipul Das; Ravi Soni; Mate Fejes; Sohan Ranjan; Daniel Attila Szabo; Vikram Melapudi; K. S. Shriram; Utkarsh Agrawal; László Ruskó; Zita Herczeg; Barbara Darázs; et al. (MICCAI (7), 2021)

Multi-modal trained artificial intelligence solution to triage chest X-ray for COVID-19 using pristine ground-truth, versus radiologists. - Tao Tan; Bipul Das; Ravi Soni; Mate Fejes; Hongxu Yang; Sohan Ranjan; Daniel Attila Szabo; Vikram Melapudi; K. S. Shriram; Utkarsh Agrawal; László Ruskó; Zita Herczeg; et al. (Neurocomputing, 2022)

Modality-Independent Explainable Detection of Inaccurate Organ Segmentations Using Denoising Autoencoders. - Levente Lippenszky; István Megyeri; Krisztian Koos; Zsófia Karancsi; Borbála Deák-Karancsi; András Frontó; Makk Árpád; Attila Rádics; Erhan Bas; László Ruskó (CoRR, 2025)