Journal Papers
- N. Kanwal, F. Pérez-Bueno, A.Schmidt, K. Engan, and R. Molina, “The devil is in the details: Whole Slide Image acquisition and processing for artifact detection, color variation, and data augmentation. A review.”, IEEE Access, vol. 10, 58821-58844, 2022. [BibTeX entry][ (52045 KB.)][doi: 10.1109/ACCESS.2022.3176091]
- S. López-Tapia, J. Mateos, R. Molina, and A.K. Katsaggelos, “Learning Moore-Penrose Based Residuals for Robust Non-Blind Image Deconvolution”, Digital Signal Processing, 2022. [BibTeX entry] (Submitted).
- F.M. Castro-Macías, P. Morales-Álvarez, Y. Wu, R. Molina, and A.K. Katsaggelos, “Hyperbolic Secant Representation of the Logistic Function: Application to Probabilistic Multiple Instance Learning for CT Intracranial Hemorrhage Detection”, Artificial Intelligence, 2023. [BibTeX entry] (Submitted).
- S. Yang, F. Pérez-Bueno, F. M. Castro-Macías, H. Qin, R. Molina, and A. K. Katsaggelos, “Deep Variational Bayesian Stain Separation of histological images using Blind Color Deconvolution”, Digital Signal Processing Journal, April 2023. [BibTeX entry][Abstract] (Submitted).
- P. Morales-Álvarez, A. Schmidt, J.M. Hernández-Lobato, and R. Molina, “Introducing instance correlation in multiple instance learning. Application to cancer detection on histopathological images”, Pattern Recognition, May 2022. [BibTeX entry] (Submitted).
- M. López-Pérez, P. Morales-Álvarez, L. Cooper, C. Felicelli, J Goldstein, B. Vadasz , R. Molina, and A.K. Katsaggelos, “Learning from crowds for automated histopathological image segmentation”, Computerized Medical Imaging and Graphics, June 2023. [BibTeX entry](Submitted).
- N. Kanwal, M. López-Pérez, U. Kiraz, T. Zuiverloon, R. Molina, and K. Engan, “Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images”, Computerized Medical Imaging and Graphics, 2023. [BibTeX entry] (Submitted).
Conference Papers
- F. Pérez-Bueno, K. Engan, and R. Molina, “A Robust BKSVD Method for Blind Color Deconvolution and Blood Detection on H&E Histological Images” in Artificial Intelligence in Medicine (AIME), edited by Springer, vol. 13897, Portoroz (Eslovenia), June 2023. Highlighted as one of the top-3 best papers of the conference.[BibTeX entry][Abstract][ (8649 KB.)].
- M. López-Pérez, P. Morales-Álvarez, L. Cooper, R. Molina, and A.K. Katsaggelos, “Crowdsourcing segmentation of histopathological images using annotations provided by medical students” in Artificial Intelligence in Medicine (AIME), edited by Springer, 245-249, Portoroz (Slovenia), June 2023. [BibTeX entry][Abstract]
- S. Yang, F. Pérez-Bueno, F. Castro-Macías, R. Molina, and A. K. Katsaggelos, “Deep Bayesian Blind Color Deconvolution of Histological Images” in IEEE International Conference on Image Processing (ICIP), Kuala Lumpur (Malaysia), October 2023. [BibTeX entry][Abstract] (Accepted for publication).
- S. López-Tapia, J. Mateos, R. Molina, and A.K. Katsaggelos, “Deep robust image restoration using the Moore-Penrose blur inverse” in 2023 IEEE International Conference on Image Processing (ICIP 2023), Kuala Lumpur (Malaysia), October 2023. [BibTeX entry][Abstract](Accepted for publication).
- Y. Wu, F.M. Castro-Macías, P. Morales-Álvarez, R. Molina, and A.K. Katsaggelos, “Smooth Attention for Deep Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection” in International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Vancouver (Canada), October 2023. [BibTeX entry](Accepted for publication).
Theses
- M. López-Pérez, Probabilistic Methods for Image and Signal Classification. Applications to Medicine and Volcanology, Universidad de Granada, July 2022. Supervised by: R. Molina and A. K. Katsaggelos. [BibTeX entry][ (12485 KB.)]
- F. Pérez-Bueno, Improvement, Classification and Interpretation of Cancer Histological Images Using Probabilistic Models, Universidad de Granada, November 2022. Supervised by: R. Molina and V. Naranjo. [BibTeX entry][Abstract][ (115453 KB.)]