22 Result(s)
within
Pablo Márquez-Neila
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Article
Open AccessPredicting OCT biological marker localization from weak annotations
Recent developments in deep learning have shown success in accurately predicting the location of biological markers in Optical Coherence Tomography (OCT) volumes of patients with Age-Related Macular Degenerati...
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Article
Open AccessMüller matrix polarimetry for pancreatic tissue characterization
Polarimetry is an optical characterization technique capable of analyzing the polarization state of light reflected by materials and biological samples. In this study, we investigate the potential of Müller ma...
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Article
Open AccessUnsupervised out-of-distribution detection for safer robotically guided retinal microsurgery
A fundamental problem in designing safe machine learning systems is identifying when samples presented to a deployed model differ from those observed at training time. Detecting so-called out-of-distribution (...
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Chapter and Conference Paper
Domain Adaptation for Medical Image Segmentation Using Transformation-Invariant Self-training
Models capable of leveraging unlabelled data are crucial in overcoming large distribution gaps between the acquired datasets across different imaging devices and configurations. In this regard, self-training t...
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Chapter and Conference Paper
Localized Questions in Medical Visual Question Answering
Visual Question Answering (VQA) models aim to answer natural language questions about given images. Due to its ability to ask questions that differ from those used when training the model, medical VQA has rece...
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Chapter and Conference Paper
SS3D: Unsupervised Out-of-Distribution Detection and Localization for Medical Volumes
We present an extension of the self-supervised outlier detection (SSD) framework [12] to the three-dimensional case. We first apply contrastive learning on a network using a general dataset of two-dimensional sli...
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Chapter and Conference Paper
Consistency-Preserving Visual Question Answering in Medical Imaging
Visual Question Answering (VQA) models take an image and a natural-language question as input and infer the answer to the question. Recently, VQA systems in medical imaging have gained popularity thanks to pot...
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Chapter and Conference Paper
Data Invariants to Understand Unsupervised Out-of-Distribution Detection
Unsupervised out-of-distribution (U-OOD) detection has recently attracted much attention due to its importance in mission-critical systems and broader applicability over its supervised counterpart. Despite thi...
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Article
Open AccessMask then classify: multi-instance segmentation for surgical instruments
The detection and segmentation of surgical instruments has been a vital step for many applications in minimally invasive surgical robotics. Previously, the problem was tackled from a semantic segmentation pers...
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Article
Open AccessAssessment of patient specific information in the wild on fundus photography and optical coherence tomography
In this paper we analyse the performance of machine learning methods in predicting patient information such as age or sex solely from retinal imaging modalities in a heterogeneous clinical population. Our data...
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Chapter and Conference Paper
CataNet: Predicting Remaining Cataract Surgery Duration
Cataract surgery is a sight saving surgery that is performed over 10 million times each year around the world. With such a large demand, the ability to organize surgical wards and operating rooms efficiently i...
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Article
Real-time camera pose estimation for sports fields
Given an image sequence featuring a portion of a sports field filmed by a moving and uncalibrated camera, such as the one of the smartphones, our goal is to compute automatically in real time the focal length ...
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Article
Open AccessExpert-level Automated Biomarker Identification in Optical Coherence Tomography Scans
In ophthalmology, retinal biological markers, or biomarkers, play a critical role in the management of chronic eye conditions and in the development of new therapeutics. While many imaging technologies used today...
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Chapter and Conference Paper
Image Data Validation for Medical Systems
Data validation is the process of ensuring that the input to a data processing pipeline is correct and useful. It is a critical part of software systems running in production. Image processing systems are no ...
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Chapter and Conference Paper
Deep Multi-label Classification in Affine Subspaces
Multi-label classification (MLC) problems are becoming increasingly popular in the context of medical imaging. This has in part been driven by the fact that acquiring annotations for MLC is far less burdensome...
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Chapter and Conference Paper
Fused Detection of Retinal Biomarkers in OCT Volumes
Optical Coherence Tomography (OCT) is the primary imaging modality for detecting pathological biomarkers associated to retinal diseases such as Age-Related Macular Degeneration. In practice, clinical diagnosis...
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Article
Supervised machine learning for analysing spectra of exoplanetary atmospheres
The use of machine learning is becoming ubiquitous in astronomy1–3, but remains rare in the study of the atmospheres of exoplanets. Given the spectrum of an exoplanetary atmosphere, a multi-parameter space is swe...
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Article
Open AccessA Fast Method for the Segmentation of Synaptic Junctions and Mitochondria in Serial Electron Microscopic Images of the Brain
Recent electron microscopy (EM) imaging techniques permit the automatic acquisition of a large number of serial sections from brain samples. Manual segmentation of these images is tedious, time-consuming and r...
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Article
Speeding-up homography estimation in mobile devices
A critical problem faced by computer vision on mobile devices is reducing the computational cost of algorithms and avoiding visual stalls. In this paper, we introduce a procedure for reducing the number of sam...
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Article
Rationalizing Efficient Compositional Image Alignment
We study the issue of computational efficiency for Gauss-Newton (GN) non-linear least-squares optimization in the context of image alignment. We introduce the Constant Jacobian Gauss-Newton (CJGN) optimization, a...
