Browsing by Author "Vilaplana Besler, Verónica"
Now showing items 1-20 of 154
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3D convolutional neural networks for brain tumor segmentation
(2016)
Conference lecture
Restricted access - publisher's policyThis paper presents our work on applying 3D Convolutional Networks for brain tumor segmentation for the BRATS challenge. We are currently experimenting with different 3D fully convolutional architectures. We present ... -
3D convolutional neural networks for brain tumor segmentation: a comparison of multi-resolution architectures
(Springer, 2017-04-24)
Part of book or chapter of book
Open Access -
A dual network for super-resolution and semantic segmentation of sentinel-2 imagery
(Multidisciplinary Digital Publishing Institute (MDPI), 2021-11-12)
Article
Open AccessThere is a growing interest in the development of automated data processing workflows that provide reliable, high spatial resolution land cover maps. However, high-resolution remote sensing images are not always affordable. ... -
A morphological approach for segmentation and tracking of human faces
(Barcelona, 2000)
Conference lecture
Open AccessA new technique for segmenting and tracking human faces in video sequences is presented. The technique relies on morphological tools such as using connected operators to extract the connected component that more likely ... -
Action tube extraction based 3D-CNN for RGB-D action recognition
(Institute of Electrical and Electronics Engineers (IEEE), 2018)
Conference report
Open AccessIn this paper we propose a novel action tube extractor for RGB-D action recognition in trimmed videos. The action tube extractor takes as input a video and outputs an action tube. The method consists of two parts: spatial ... -
AmodalAppleSize_RGB-D dataset: RGB-D images of apple trees annotated with modal and amodal segmentation masks for fruit detection, visibility and size estimation
(Elsevier, 2024-02)
Article
Open AccessThe present dataset comprises a collection of RGB-D apple tree images that can be used to train and test computer vision-based fruit detection and sizing methods. This dataset encompasses two distinct sets of data obtained ... -
Automatic keyframe selection based on mutual reinforcement algorithm
(Institute of Electrical and Electronics Engineers (IEEE), 2013)
Conference report
Restricted access - publisher's policyThis paper addresses the problem of video summarization through an automatic selection of a single representative keyframe. The proposed solution is based on the mutual reinforcement paradigm, where a keyframe is selected ... -
BCN20000: dermoscopic lesions in the wild
(2019)
Research report
Open AccessThis article summarizes the BCN20000 dataset, composed of 19424 dermoscopic images of skin lesions captured from 2010 to 2016 in the facilities of the Hospital Clínic in Barcelona. With this dataset, we aim to study the ... -
BCN20000: dermoscopic lesions in the wild
(Nature, 2024-06-17)
Article
Open AccessAdvancements in dermatological artificial intelligence research require high-quality and comprehensive datasets that mirror real-world clinical scenarios. We introduce a collection of 18,946 dermoscopic images spanning ... -
Benchmark on automatic 6-month-old infant brain segmentation algorithms: the iSeg-2017 challenge
(2019-02-27)
Article
Open AccessAccurate segmentation of infant brain magnetic resonance (MR) images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) is an indispensable foundation for early studying of brain growth patterns and ... -
Biological brain age prediction using machine learning on structural neuroimaging data: Multi-cohort validation against biomarkers of Alzheimer’s disease and neurodegeneration stratified by sex
(2022-06-28)
Research report
Open AccessBrain-age can be inferred from structural neuroimaging and compared to chronological age (brain-age delta) as a marker of biological brain aging. Accelerated aging has been found in neurodegenerative disorders like Alzheimer’s ... -
Biological brain age prediction using machine learning on structural neuroimaging data: multi-cohort validation against biomarkers of Alzheimer's disease and neurodegeneration stratified by sex
(2023-05-12)
Article
Open AccessBrain-age can be inferred from structural neuroimaging and compared to chronological age (brain-age delta) as a marker of biological brain aging. Accelerated aging has been found in neurodegenerative disorders like Alzheimer's ... -
Biological brain age prediction using machine learning on structural neuroimaging data: Multi-cohort validation against biomarkers of Alzheimer’s disease and neurodegeneration
(Elsevier, 2022-12-20)
Article
Open AccessBackground: Brain-age can be inferred from structural neuroimaging and compared to chronological age (brain-age delta), as a marker of accelerated/decelerated biological brain aging. Accelerated biological aging has ... -
Brain MRI super-resolution using generative adversarial networks
(2018)
Conference lecture
Open AccessIn this work we propose an adversarial learning approach to generate high resolution MRI scans from low resolution images. The architecture, based on the SRGAN model, adopts 3D convolutions to exploit volumetric information. ... -
Brain structural alterations in cognitively unimpaired individuals with discordant amyloid-ß PET and CSF Aß42 status: findings using machine learning
(Wiley, 2021-12)
Article
Open AccessBackground: CSF Aß42 is thought to show AD-related alterations earlier than amyloid-ß PET. Therefore, cognitively unimpaired (CU) individuals with abnormal CSF Aß42 and normal amyloid-ß PET are believed to be in the ... -
Brain-age mediates the association between modifiable risk factors and cognitive decline early in the AD continuum
(Wiley, 2023-12)
Article
Open AccessBackground: Neuroimaging-derived brain-age is a useful biomarker to study the brain’s biological aging process. Brain-age has shown cross-sectional associations with cognitive function and modifiable risk factors for ... -
Brain-age prediction and its associations with glial and synaptic CSF markers
(Wiley, 2023-12)
Article
Open AccessBackground: MRI-derived brain-age prediction is a promising biomarker of biological brain aging. Accelerated brain aging has been found in Alzheimer’s disease (AD) and other neurodegenerative diseases. However, no ... -
Breast cancer molecular subtyping from H&E whole slide images using foundation models and transformers
(2024-10)
Part of book or chapter of book
Restricted access - publisher's policyThis study tackles the challenge of classifying breast cancer molecular subtypes using H&E-stained Whole Slide Images (WSI), avoiding the cost and labor limitations of the commonly used immunohistochemistry. We leverage ... -
Bridging domains in melanoma diagnostics: predicting BRAF mutations and sentinel lymph node positivity with attention-based models in histological images
(Institute of Electrical and Electronics Engineers (IEEE), 2024)
Conference lecture
Open AccessWhole Slide Images (WSIs) have significantly advanced the field of pathology by providing highly detailed views of tissue samples. Integrating Deep Learning (DL) into this area of research, particularly through transformer-based ... -
Caption text extraction for indexing purposes using a hierarchical region-based image model
(2010-02-17)
Conference lecture
Open AccessThis paper presents a technique for detecting caption text for indexing purposes. This technique is to be included in a generic indexing system dealing with other semantic concepts. The various object detection algorithms ...
