Publicaciones (314) Publicaciones de RAFAEL MOLINA SORIANO

2024

  1. An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection

    Expert Systems with Applications, Vol. 240

  2. Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images

    Computerized Medical Imaging and Graphics, Vol. 112

  3. BCD-net: Stain separation of histological images using deep variational Bayesian blind color deconvolution

    Digital Signal Processing: A Review Journal, Vol. 145

  4. Focused active learning for histopathological image classification

    Medical Image Analysis, Vol. 95

  5. Hyperbolic Secant representation of the logistic function: Application to probabilistic Multiple Instance Learning for CT intracranial hemorrhage detection

    Artificial Intelligence, Vol. 331

  6. Learning from crowds for automated histopathological image segmentation

    Computerized Medical Imaging and Graphics, Vol. 112

2023

  1. A Robust BKSVD Method for Blind Color Deconvolution and Blood Detection on H &E Histological Images

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset

    Artificial Intelligence in Medicine, Vol. 145

  3. Crowdsourcing Segmentation of Histopathological Images Using Annotations Provided by Medical Students

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  4. Deep Bayesian Blind Color Deconvolution of Histological Images

    Proceedings - International Conference on Image Processing, ICIP

  5. Deep Gaussian Processes for Classification With Multiple Noisy Annotators. Application to Breast Cancer Tissue Classification

    IEEE Access, Vol. 11, pp. 6922-6934

  6. Deep Robust Image Restoration Using the Moore-Penrose Blur Inverse

    Proceedings - International Conference on Image Processing, ICIP

  7. Learning Moore-Penrose based residuals for robust non-blind image deconvolution

    Digital Signal Processing: A Review Journal, Vol. 142

  8. Probabilistic Attention Based on Gaussian Processes for Deep Multiple Instance Learning

    IEEE Transactions on Neural Networks and Learning Systems

  9. Probabilistic Modeling of Inter- and Intra-observer Variability in Medical Image Segmentation

    Proceedings of the IEEE International Conference on Computer Vision

  10. Probabilistic fusion of crowds and experts for the search of gravitational waves

    Knowledge-Based Systems, Vol. 261

  11. Smooth Attention for Deep Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2022

  1. Bayesian K-SVD for H and E blind color deconvolution. Applications to stain normalization, data augmentation and cancer classification

    Computerized Medical Imaging and Graphics, Vol. 97

  2. Deep Gaussian processes for multiple instance learning: Application to CT intracranial hemorrhage detection

    Computer Methods and Programs in Biomedicine, Vol. 219

  3. Efficient Cancer Classification by Coupling Semi Supervised and Multiple Instance Learning

    IEEE Access, Vol. 10, pp. 9763-9773