9 citations · 17 across the 12 of their papers we have counts for
12 papers
Initialization matters in few-shot adaptation of vision-language models for histopathological image classification
Pablo Meseguer, Rocío del Amor, Valery Naranjo
Vision language models (VLM) pre-trained on datasets of histopathological image-caption pairs enabled zero-shot slide-level classification. The ability of VLM image encoders to ext…
Masked Autoencoder Joint Learning for Robust Spitzoid Tumor Classification
Ilán Carretero, Roshni Mahtani, Silvia Perez-Deben +4
Accurate diagnosis of spitzoid tumors (ST) is critical to ensure a favorable prognosis and to avoid both under- and over-treatment. Epigenetic data, particularly DNA methylation, p…
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…
MID-INFRARED (MIR) OCT-based inspection in industry
N. P. García-de-la-Puente, Rocío del Amor, Fernando García-Torres +9
This paper aims to evaluate mid-infrared (MIR) Optical Coherence Tomography (OCT) systems as a tool to penetrate different materials and detect sub-surface irregularities. This is…
Reinforcement Learning for Synchronised Flow Control in a Dual-Gate Resin Infusion System
Miguel Camacho-Sánchez, Fernando García-Torres, Jesper John Lisegaard +3
Resin infusion (RI) and resin transfer moulding (RTM) are critical processes for the manufacturing of high-performance fibre-reinforced polymer composites, particularly for large-s…
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…
A Deep Embedded Refined Clustering Approach for Breast Cancer Distinction based on DNA Methylation
del Amor Rocío, Colomer Adrián, Monteagudo Carlos +1
Epigenetic alterations have an important role in the development of several types of cancer. Epigenetic studies generate a large amount of data, which makes it essential to develop…
Glaucoma Detection From Raw Circumapillary OCT Images Using Fully Convolutional Neural Networks
Gabriel García, Rocío del Amor, Adrián Colomer +1
Nowadays, glaucoma is the leading cause of blindness worldwide. We propose in this paper two different deep-learning-based approaches to address glaucoma detection just from raw ci…