2 citations · 3 across the 8 of their papers we have counts for
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Do Center Biases Propagate? Robustness of Pathology Foundation Models in Whole-Slide Image Classification
Ilán Carretero, Pablo Meseguer, Rocío del Amor +1
Pathology foundation models (PFMs) have transformed computational pathology through powerful representation learning from histopathological images. PFMs provide rich, discriminativ…
OPAL: Orthonormal Prototype Alignment Learning for Interpretable Image Classification
Ilán Carretero, Gustavo Jesús Angulo, Rocío del Amor +1
Prototypical part-based models provide explainable predictions by comparing input regions to learned prototypes. However, current approaches are burdened by complex, multi-stage tr…
DualDiT: A Conditional Dual-Output Diffusion Transformer for Joint OCT Image and Segmentation Mask Generation
Fernando García-Torres, Rocío del Amor, Sandra Morales +4
Background and Objective: Generating realistic medical images with anatomically accurate segmentation masks helps address the shortage of annotated data in medical imaging, particu…
Zero-shot segmentation of skin tumors in whole-slide images with vision-language foundation models
Santiago Moreno, Pablo Meseguer, Rocío del Amor +1
Accurate annotation of cutaneous neoplasm biopsies represents a major challenge due to their wide morphological variability, overlapping histological patterns, and the subtle disti…
Benchmarking histopathology foundation models in a multi-center dataset for skin cancer subtyping
Pablo Meseguer, Rocío del Amor, Valery Naranjo
Pretraining on large-scale, in-domain datasets grants histopathology foundation models (FM) the ability to learn task-agnostic data representations, enhancing transfer learning on…
Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma
Alvaro Pastor-Naranjo, Pablo Meseguer, Rocío del Amor +6
Ewing's sarcoma (ES), characterized by a high density of small round blue cells without structural organization, presents a significant health concern, particularly among adolescen…
Enhancing Whole Slide Image Classification through Supervised Contrastive Domain Adaptation
Ilán Carretero, Pablo Meseguer, Rocío del Amor +1
Domain shift in the field of histopathological imaging is a common phenomenon due to the intra- and inter-hospital variability of staining and digitization protocols. The implement…
Foundation Models for Slide-level Cancer Subtyping in Digital Pathology
Pablo Meseguer, Rocío del Amor, Adrian Colomer +1
Since the emergence of the ImageNet dataset, the pretraining and fine-tuning approach has become widely adopted in computer vision due to the ability of ImageNet-pretrained models…
MI-VisionShot: Few-shot adaptation of vision-language models for slide-level classification of histopathological images
Pablo Meseguer, Rocío del Amor, Valery Naranjo
Vision-language supervision has made remarkable strides in learning visual representations from textual guidance. In digital pathology, vision-language models (VLM), pre-trained on…