A5043316752- AI in cancer detection
- Retinal Imaging and Analysis
- Digital Imaging for Blood Diseases
- Glaucoma and retinal disorders
- Medical Image Segmentation Techniques
- Radiomics and Machine Learning in Medical Imaging
- Colorectal Cancer Screening and Detection
- Cell Image Analysis Techniques
- Optical Coherence Tomography Applications
- Cutaneous Melanoma Detection and Management
- Retinal Diseases and Treatments
- Image Retrieval and Classification Techniques
- Advanced Neural Network Applications
- Inflammatory Bowel Disease
- Spectroscopy Techniques in Biomedical and Chemical Research
- Medical Imaging Techniques and Applications
- Medical Imaging and Analysis
- Advanced Vision and Imaging
- COVID-19 diagnosis using AI
- Spectroscopy and Chemometric Analyses
- Reproductive Biology and Fertility
- Generative Adversarial Networks and Image Synthesis
- Music and Audio Processing
- Brain Tumor Detection and Classification
- Speech and Audio Processing
Universitat Politècnica de València
2016-2025
Artificial Intelligence Research Institute
2023-2024
Universidad Carlos III de Madrid
2023
Bridge University
2023
Universitat de València
2020
Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana
2014-2018
Multimedia University
2010
Generalized nucleus segmentation techniques can contribute greatly to reducing the time develop and validate visual biomarkers for new digital pathology datasets. We summarize results of MoNuSeg 2018 Challenge whose objective was generalizable nuclei in pathology. The challenge an official satellite event MICCAI conference which 32 teams with more than 80 participants from geographically diverse institutes participated. Contestants were given a training set 30 images seven organs annotations...
Most current algorithms for automatic glaucoma assessment using fundus images rely on handcrafted features based segmentation, which are affected by the performance of chosen segmentation method and extracted features. Among other characteristics, convolutional neural networks (CNNs) known because their ability to learn highly discriminative from raw pixel intensities. In this paper, we employed five different ImageNet-trained models (VGG16, VGG19, InceptionV3, ResNet50 Xception) images....
The algorithm proposed in this paper allows to automatically segment the optic disc from a fundus image. goal is facilitate early detection of certain pathologies and fully automate process so as avoid specialist intervention. method for extraction contour mainly based on mathematical morphology along with principal component analysis (PCA). It makes use different operations such generalized distance function (GDF), variant watershed transformation, stochastic watershed, geodesic...
Recent works show that generative adversarial networks (GANs) can be successfully applied to image synthesis and semi-supervised learning, where, given a small labeled database large unlabeled database, the goal is train powerful classifier. In this paper, we trained retinal synthesizer learning method for automatic glaucoma assessment using an model on glaucoma-labeled database. Various studies have shown monitored by analyzing optic disc its surroundings, reason, images used in paper were...
Histological remission is evolving as an important treatment target in UC. We aimed to develop a simple histological index, aligned endoscopy, correlated with clinical outcomes, and suited apply artificial intelligence (AI) system evaluate inflammatory activity.Using set of 614 biopsies from 307 patients UC enrolled into prospective multicentre study, we developed the Paddington International virtual ChromoendoScopy ScOre (PICaSSO) Histologic Remission Index (PHRI). Agreement multiple other...
Estimated blind people in the world will exceed 40 million by 2025. To develop novel algorithms based on fundus image descriptors that allow automatic classification of retinal tissue into healthy and pathological early stages is necessary. In this paper, we focus one most common pathologies current society: diabetic retinopathy. The proposed method avoids necessity lesion segmentation or candidate map generation before stage. Local binary patterns granulometric profiles are locally computed...
Endoscopic and histological remission (ER, HR) are therapeutic targets in ulcerative colitis (UC). Virtual chromoendoscopy (VCE) improves endoscopic assessment the prediction of histology; however, interobserver variability limits standardized assessment. We aimed to develop an artificial intelligence (AI) tool distinguish ER/activity, predict histology risk flare from white-light endoscopy (WLE) VCE videos.1090 videos (67 280 frames) 283 patients were used a convolutional neural network...
Prostate cancer is a critical healthcare challenge globally and one of the most prevalent types in men. Early accurate diagnosis essential for effective treatment improved patient outcomes. In existing literature, computer-aided (CAD) solutions have been developed to assist pathologists various tasks, including classification, diagnosis, prostate grading. Content-based image retrieval (CBIR) techniques provide valuable approaches enhance these solutions. This study evaluates how generative...
This paper investigates discrimination capabilities in the texture of fundus images to differentiate between pathological and healthy images. For this purpose, performance local binary patterns (LBP) as a descriptor for retinal has been explored compared with other descriptors such LBP filtering phase quantization. The goal is distinguish diabetic retinopathy (DR), age-related macular degeneration (AMD), normal analyzing retina background avoiding previous lesion segmentation stage. Five...
The impact of PET on radiation therapy is held back by poor methods defining functional volumes interest. Many new software tools are being proposed for contouring target but the different approaches not adequately compared and their accuracy poorly evaluated due to illdefinition ground truth. This paper compares largest cohort date established, emerging methods, in terms variability. We emphasise spatial present a metric that addresses lack unique 30 used at 13 institutions contour VOIs...
This work focuses on finding the most discriminatory or representative features that allow to classify commercials according negative, neutral and positive effectiveness based Ace Score index. For this purpose, an experiment involving forty-seven participants was carried out. In electroencephalography (EEG), electrocardiography (ECG), Galvanic Skin Response (GSR) respiration data were acquired while subjects watching a 30-min audiovisual content. content composed by submarine documentary...
Prostate cancer is one of the main diseases affecting men worldwide. The gold standard for diagnosis and prognosis Gleason grading system. In this process, pathologists manually analyze prostate histology slides under microscope, in a high time-consuming subjective task. last years, computer-aided-diagnosis (CAD) systems have emerged as promising tool that could support daily clinical practice. Nevertheless, these are usually trained using tedious prone-to-error pixel-level annotations...
Ulcerative colitis (UC) is an inflammatory bowel disease (IBD) affecting the colon and rectum characterized by a remitting-relapsing course. To detect mucosal inflammation associated with UC, histology considered most stringent criteria. In turn, histologic remission (HR) correlates improved clinical outcomes has been recently recognized as desirable treatment target. The leading biomarker for assessing presence or absence of neutrophils. Therefore, finding this cell in specific structures...