BIGS: A framework for large-scale image processing and analysis over distributed and heterogeneous computing resources. - Raúl Ramos-Pollán; Fabio A. González 001; Juan C. Caicedo; Angel Cruz-Roa; Jorge E. Camargo; Jorge A. Vanegas; Santiago A. Perez; José David Bermeo; Juan Sebastian Otálora Montenegro; Paola K. Rozo; John Edison Arevalo Ovalle (eScience, 2012)

Online Matrix Factorization for Space Embedding Multilabel Annotation. - Juan Sebastian Otálora Montenegro; Santiago A. Pérez-Rubiano; Fabio A. González 001 (CIARP (1), 2013)

MindLab at ImageCLEF 2014: Scalable Concept Image Annotation. - Jorge A. Vanegas; John Edison Arevalo Ovalle; Juan Sebastian Otálora Montenegro; Fabian Páez; Santiago A. Pérez-Rubiano; Fabio A. González 001 (CLEF (Working Notes), 2014)

Combining Unsupervised Feature Learning and Riesz Wavelets for Histopathology Image Representation: Application to Identifying Anaplastic Medulloblastoma. - Sebastian Otálora; Angel Cruz-Roa; John Edison Arevalo Ovalle; Manfredo Atzori; Anant Madabhushi; Alexander R. Judkins; Fabio A. González 001; Henning Müller; Adrien Depeursinge (MICCAI (1), 2015)

Training Deep Convolutional Neural Networks with Active Learning for Exudate Classification in Eye Fundus Images. - Sebastian Otálora; Oscar J. Perdomo; Fabio A. González 001; Henning Müller (CVII-STENT/LABELS@MICCAI, 2017)

Deep Multimodal Case-Based Retrieval for Large Histopathology Datasets. - Oscar Alfonso Jiménez del Toro; Sebastian Otálora; Manfredo Atzori; Henning Müller (Patch-MI@MICCAI, 2017)

Convolutional neural networks for an automatic classification of prostate tissue slides with high-grade Gleason score. - Oscar Alfonso Jiménez del Toro; Manfredo Atzori; Sebastian Otálora; Mats Andersson; Kristian Eurén; Martin Hedlund; Peter Rönnquist; Henning Müller (Digital Pathology, 2017)

Determining the scale of image patches using a deep learning approach. - Sebastian Otálora; Oscar J. Perdomo; Manfredo Atzori; Mats Andersson; Ludwig Jacobsson; Martin Hedlund; Henning Müller (ISBI, 2018)

OCT-NET: A convolutional network for automatic classification of normal and diabetic macular edema using sd-oct volumes. - Oscar J. Perdomo; Sebastian Otálora; Fabio A. González 001; Fabrice Mériaudeau; Henning Müller (ISBI, 2018)

Image Magnification Regression Using DenseNet for Exploiting Histopathology Open Access Content. - Sebastian Otálora; Manfredo Atzori; Vincent Andrearczyk; Henning Müller (COMPAY/OMIA@MICCAI, 2018)

A Deep Learning Mechanism for Efficient Information Dissemination in Vehicular Floating Content. - Gaetano Manzo; Juan Sebastian Otálora Montenegro; Gianluca Rizzo (CoRR, 2018)

A Deep Learning Strategy for Vehicular Floating Content Management. - Gaetano Manzo; Juan Sebastian Otálora Montenegro; Marco Ajmone Marsan; Gianluca Rizzo (SIGMETRICS Perform. Evaluation Rev., 2018)

Automatic Creation of a Pharmaceutical Corpus Based on Open-Data. - Cristian Bravo; Sebastian Otálora; Sonia Ordoñez-Salinas (CICLing (1), 2019)

DeepFloat: Resource-Efficient Dynamic Management of Vehicular Floating Content. - Gaetano Manzo; Sebastian Otálora; Torsten Braun; Marco Ajmone Marsan; Gianluca Rizzo; Hung Nguyen 004 (ITC, 2019)

Classification of diabetes-related retinal diseases using a deep learning approach in optical coherence tomography. - Oscar J. Perdomo; Hernán Rios; Francisco J. Rodríguez 004; Juan Sebastian Otálora Montenegro; Fabrice Mériaudeau; Henning Müller; Fabio A. González 001 (Comput. Methods Programs Biomed., 2019)

Fusing learned representations from Riesz Filters and Deep CNN for lung tissue classification. - Ranveer Joyseeree; Sebastian Otálora; Henning Müller; Adrien Depeursinge (Medical Image Anal., 2019)

Classification of Noisy Free-Text Prostate Cancer Pathology Reports Using Natural Language Processing. - Anjani Dhrangadhariya; Sebastian Otálora; Manfredo Atzori; Henning Müller (ICPR Workshops (1), 2020)

Semi-supervised Learning with a Teacher-Student Paradigm for Histopathology Classification: A Resource to Face Data Heterogeneity and Lack of Local Annotations. - Niccolò Marini; Sebastian Otálora; Henning Müller; Manfredo Atzori (ICPR Workshops (1), 2020)

Multimodal Latent Semantic Alignment for Automated Prostate Tissue Classification and Retrieval. - Juan S. Lara; Victor H. Contreras O.; Sebastian Otálora; Henning Müller; Fabio A. González 001 (MICCAI (5), 2020)

Semi-weakly Supervised Learning for Prostate Cancer Image Classification with Teacher-Student Deep Convolutional Networks. - Sebastian Otálora; Niccolò Marini; Henning Müller; Manfredo Atzori (iMIMIC/MIL3ID/LABELS@MICCAI, 2020)

Generalizing convolution neural networks on stain color heterogeneous data for computational pathology. - Amjad Khan 002; Manfredo Atzori; Sebastian Otálora; Vincent Andrearczyk; Henning Müller (Digital Pathology, 2020)

Systematic comparison of deep learning strategies for weakly supervised Gleason grading. - Sebastian Otálora; Manfredo Atzori; Amjad Khan 002; Oscar Alfonso Jiménez del Toro; Vincent Andrearczyk; Henning Müller (Digital Pathology, 2020)

Guiding CNNs towards Relevant Concepts by Multi-task and Adversarial Learning. - Mara Graziani; Sebastian Otálora; Henning Müller; Vincent Andrearczyk (CoRR, 2020)

Multi-Scale Task Multiple Instance Learning for the Classification of Digital Pathology Images with Global Annotations. - Niccolò Marini; Sebastian Otálora; Francesco Ciompi; Gianmaria Silvello; Stefano Marchesin 001; Simona Vatrano; Genziana Buttafuoco; Manfredo Atzori; Henning Müller (COMPAY@MICCAI, 2021)

H&E-adversarial network: a convolutional neural network to learn stain-invariant features through Hematoxylin & Eosin regression. - Niccolò Marini; Manfredo Atzori; Sebastian Otálora; Stéphane Marchand-Maillet; Henning Müller (ICCVW, 2021)

Combining weakly and strongly supervised learning improves strong supervision in Gleason pattern classification. - Sebastian Otálora; Niccolò Marini; Henning Müller; Manfredo Atzori (BMC Medical Imaging, 2021)

Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images. - Niccolò Marini; Sebastian Otálora; Damian Podareanu; Mart van Rijthoven; Jeroen van der Laak; Francesco Ciompi; Henning Müller; Manfredo Atzori (Frontiers Comput. Sci., 2021)

Semi-supervised training of deep convolutional neural networks with heterogeneous data and few local annotations: An experiment on prostate histopathology image classification. - Niccolò Marini; Sebastian Otálora; Henning Müller; Manfredo Atzori (Medical Image Anal., 2021)

Deep Learning for Histopathology Image Analysis From Heterogeneous and Multimodal Data Sources. - Juan Sebastian Otálora Montenegro (2021)

Weighting Schemes for Federated Learning in Heterogeneous and Imbalanced Segmentation Datasets. - Sebastian Otálora; Jonathan Rafael-Patino; Antoine Madrona; Elda Fischi Gomez; Veronica Ravano; Tobias Kober; Søren Christensen; Arsany Hakim; Roland Wiest; Jonas Richiardi; Richard McKinley (BrainLes@MICCAI, 2022)

Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations. - Niccolò Marini; Stefano Marchesin 001; Sebastian Otálora; Marek Wodzinski; Alessandro Caputo; Mart van Rijthoven; Witali Aswolinskiy; John-Melle Bokhorst; Damian Podareanu; Edyta Petters; Svetla Boytcheva; Genziana Buttafuoco; et al. (npj Digit. Medicine, 2022)

Federated Learning on Heterogeneous Diffusion-Weighted Imaging Data for Acute Stroke Infarct Segmentation. - Antoine Madrona; Sebastian Otálora; Elda Fischi Gomez; Veronica Ravano; Bénédicte Maréchal; Jean-Philippe Thiran; Tobias Kober; Roland Wiest; Richard McKinley; Jonas Richiardi; Jonathan Rafael-Patino (ISBI, 2023)

Training state-of-the-art pathology foundation models with orders of magnitude less data. - Mikhail Karasikov; Joost van Doorn; Nicolas Känzig; Melis Erdal Cesur; Hugo Mark Horlings; Robert B. West; Fei Tang; Sebastian Otálora (CoRR, 2025)