Adrián Colomer
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View article: Defect Segmentation in OCT scans of ceramic parts for non-destructive inspection using deep learning
Defect Segmentation in OCT scans of ceramic parts for non-destructive inspection using deep learning Open
Non-destructive testing (NDT) is essential in ceramic manufacturing to ensure the quality of components without compromising their integrity. In this context, Optical Coherence Tomography (OCT) enables high-resolution internal imaging, rev…
View article: A clinical study of two optical coherence tomography scanners – how resolution and depth affect skin cancer diagnostic accuracy classified by deep neural networks and foundation models
A clinical study of two optical coherence tomography scanners – how resolution and depth affect skin cancer diagnostic accuracy classified by deep neural networks and foundation models Open
Early and accurate detection of skin cancer is essential to ensure effective treatment of patients. For this purpose, non-invasive bedside imaging technologies such as optical coherence tomography (OCT) are emerging in dermatology. Like ul…
View article: BlastDiffusion: A Latent Diffusion Model for Generating Synthetic Embryo Images to Address Data Scarcity in In Vitro Fertilization
BlastDiffusion: A Latent Diffusion Model for Generating Synthetic Embryo Images to Address Data Scarcity in In Vitro Fertilization Open
Accurately identifying oocytes that progress to the blastocyst stage is crucial in reproductive medicine, but the limited availability of annotated high-quality embryo images presents challenges for developing automated diagnostic tools. T…
View article: Enhancing Image Retrieval Performance With Generative Models in Siamese Networks
Enhancing Image Retrieval Performance With Generative Models in Siamese Networks Open
Prostate cancer is a critical healthcare challenge globally and is one of the most prevalent types of cancer in men. Early and accurate diagnosis is essential for effective treatment and improved patient outcomes. In the existing literatur…
View article: A Transparent Search-Based Framework for Skin and Breast Cancer Diagnosis Using Siamese Networks
A Transparent Search-Based Framework for Skin and Breast Cancer Diagnosis Using Siamese Networks Open
Computer aid diagnosis has developed digital pathology with Deep Learning (DL)-based tools to assist pathologists in decision-making. Content-Based Histopathological Image Retrieval (CBHIR) is a novel tool to seek highly correlated patches…
View article: Foundation Models for Slide-level Cancer Subtyping in Digital Pathology
Foundation Models for Slide-level Cancer Subtyping in Digital Pathology Open
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 to learn a wide variety of visual features. However, a sign…
View article: Histological interpretation of spitzoid tumours: an extensive machine learning‐based concordance analysis for improving decision making
Histological interpretation of spitzoid tumours: an extensive machine learning‐based concordance analysis for improving decision making Open
The histopathological classification of melanocytic tumours with spitzoid features remains a challenging task. We confront the complexities involved in the histological classification of these tumours by proposing machine learning (ML) alg…
View article: Deep learning methodologies for spitzoid melanocytic tumor characterization
Deep learning methodologies for spitzoid melanocytic tumor characterization Open
The digitization of biopsies into high-resolution whole-slide images has opened the way to artificial intelligence methods in pathology. While histopathological analysis of biopsies remains the gold standard for cancer diagnosis, deep lear…
View article: Advancing Content-Based Histopathological Image Retrieval Pre-Processing: A Comparative Analysis of the Effects of Color Normalization Techniques
Advancing Content-Based Histopathological Image Retrieval Pre-Processing: A Comparative Analysis of the Effects of Color Normalization Techniques Open
Content-Based Histopathological Image Retrieval (CBHIR) is a search technique based on the visual content and histopathological features of whole-slide images (WSIs). CBHIR tools assist pathologists to obtain a faster and more accurate can…
View article: Siamese Content-based Search Engine for a More Transparent Skin and Breast Cancer Diagnosis through Histological Imaging
Siamese Content-based Search Engine for a More Transparent Skin and Breast Cancer Diagnosis through Histological Imaging Open
Computer Aid Diagnosis (CAD) has developed digital pathology with Deep Learning (DL)-based tools to assist pathologists in decision-making. Content-Based Histopathological Image Retrieval (CBHIR) is a novel tool to seek highly correlated p…
View article: Optimizing Deep Learning Models for Edge Computing in Histopathology: Bridging the Gap to Clinical Practice
Optimizing Deep Learning Models for Edge Computing in Histopathology: Bridging the Gap to Clinical Practice Open
View article: Siamese Content-Based Search Engine for a More Transparent Skin and Breast Cancer Diagnosis Through Histological Imaging
Siamese Content-Based Search Engine for a More Transparent Skin and Breast Cancer Diagnosis Through Histological Imaging Open
View article: Improving the quality of image generation in art with top-k training and cyclic generative methods
Improving the quality of image generation in art with top-k training and cyclic generative methods Open
The creation of artistic images through the use of Artificial Intelligence is an area that has been gaining interest in recent years. In particular, the ability of Neural Networks to separate and subsequently recombine the style of differe…
View article: A Spitzoid Tumor dataset with clinical metadata and Whole Slide Images for Deep Learning models
A Spitzoid Tumor dataset with clinical metadata and Whole Slide Images for Deep Learning models Open
Spitzoid tumors (ST) are a group of melanocytic tumors of high diagnostic complexity. Since 1948, when Sophie Spitz first described them, the diagnostic uncertainty remains until now, especially in the intermediate category known as Spitz …
View article: WWFedCBMIR: World-Wide Federated Content-Based Medical Image Retrieval
WWFedCBMIR: World-Wide Federated Content-Based Medical Image Retrieval Open
The paper proposes a federated content-based medical image retrieval (FedCBMIR) tool that utilizes federated learning (FL) to address the challenges of acquiring a diverse medical data set for training CBMIR models. CBMIR is a tool to find…
View article: Attention to Detail: Inter-Resolution Knowledge Distillation
Attention to Detail: Inter-Resolution Knowledge Distillation Open
The development of computer vision solutions for gigapixel images in digital\npathology is hampered by significant computational limitations due to the large\nsize of whole slide images. In particular, digitizing biopsies at high\nresoluti…
View article: El rol de la inteligencia artificial generativa en la educación: beneficios potenciales de ChatGPT para promover el aprendizaje en tareas de programación en Python
El rol de la inteligencia artificial generativa en la educación: beneficios potenciales de ChatGPT para promover el aprendizaje en tareas de programación en Python Open
Una de las condiciones esenciales para el éxito del proceso de aprendizaje del alumnado es la posibilidad de acceder a recursos que le permitan aclarar sus dudas a la hora de abordar las actividades propuestas por el equipo docente. Las nu…
View article: Deep learning system for classification of ploidy status using time-lapse videos
Deep learning system for classification of ploidy status using time-lapse videos Open
This article proposes an artificial intelligence solution for prioritizing euploid embryo transfer. We can highlight the identification of a noninvasive method for chromosomal status diagnosis using a deep learning approach that analyzes r…
View article: ProGleason-GAN: Conditional progressive growing GAN for prostatic cancer Gleason grade patch synthesis
ProGleason-GAN: Conditional progressive growing GAN for prostatic cancer Gleason grade patch synthesis Open
View article: Towards More Transparent and Accurate Cancer Diagnosis with an Unsupervised CAE Approach
Towards More Transparent and Accurate Cancer Diagnosis with an Unsupervised CAE Approach Open
Background: Digital pathology has significantly impacted the cancer diagnosis field, with Content-Based Medical Image Retrieval (CBMIR) emerging as a powerful tool for analyzing histopathological Whole Slide Images (WSIs). CBMIR allows use…
View article: Towards More Transparent and Accurate Cancer Diagnosis with an Unsupervised CAE Approach
Towards More Transparent and Accurate Cancer Diagnosis with an Unsupervised CAE Approach Open
Digital pathology has revolutionized cancer diagnosis by leveraging Content-Based Medical Image Retrieval (CBMIR) for analyzing histopathological Whole Slide Images (WSIs). CBMIR enables searching for similar content, enhancing diagnostic …
View article: WWFedCBMIR: World-Wide Federated Content-Based Medical Image Retrieval
WWFedCBMIR: World-Wide Federated Content-Based Medical Image Retrieval Open
The paper proposes a Federated Content-Based Medical Image Retrieval (FedCBMIR) platform that utilizes Federated Learning (FL) to address the challenges of acquiring a diverse medical data set for training CBMIR models. CBMIR assists patho…
View article: Federating Medical Deep Learning Models from Private Jupyter Notebooks to Distributed Institutions
Federating Medical Deep Learning Models from Private Jupyter Notebooks to Distributed Institutions Open
Deep learning-based algorithms have led to tremendous progress over the last years, but they face a bottleneck as their optimal development highly relies on access to large datasets. To mitigate this limitation, cross-silo federated learni…
View article: Unsupervised Defect Detection for Infrastructure Inspection
Unsupervised Defect Detection for Infrastructure Inspection Open
View article: Toward More Transparent and Accurate Cancer Diagnosis With an Unsupervised CAE Approach
Toward More Transparent and Accurate Cancer Diagnosis With an Unsupervised CAE Approach Open
[EN] According to the Global Cancer Observatory, 2020, breast cancer is the most prevalent\ncancer type in both genders (11.7%), while prostate cancer is the second most common cancer type in\nmen (14.1%). In digital pathology, Content-Bas…
View article: Choosing Only the Best Voice Imitators: Top-K Many-to-Many Voice Conversion with Stargan-Vc
Choosing Only the Best Voice Imitators: Top-K Many-to-Many Voice Conversion with Stargan-Vc Open
View article: Deep Learning for Skin Melanocytic Tumors in Whole-Slide Images: A Systematic Review
Deep Learning for Skin Melanocytic Tumors in Whole-Slide Images: A Systematic Review Open
The rise of Artificial Intelligence (AI) has shown promising performance as a support tool in clinical pathology workflows. In addition to the well-known interobserver variability between dermatopathologists, melanomas present a significan…
View article: Constrained multiple instance learning for ulcerative colitis prediction using histological images
Constrained multiple instance learning for ulcerative colitis prediction using histological images Open
View article: Automatic characterization of human embryos at day 4 post-insemination from time-lapse imaging using supervised contrastive learning and inductive transfer learning techniques
Automatic characterization of human embryos at day 4 post-insemination from time-lapse imaging using supervised contrastive learning and inductive transfer learning techniques Open
View article: HARVIS: dynamic rerouting assistant using deep learning techniques for Single Pilot Operations (SPO)
HARVIS: dynamic rerouting assistant using deep learning techniques for Single Pilot Operations (SPO) Open