Search Results for author: Alvaro Fernandez-Quilez

Found 9 papers, 1 papers with code

Leveraging multi-view data without annotations for prostate MRI segmentation: A contrastive approach

no code implementations12 Aug 2023 Tim Nikolass Lindeijer, Tord Martin Ytredal, Trygve Eftestøl, Tobias Nordström, Fredrik Jäderling, Martin Eklund, Alvaro Fernandez-Quilez

Further, our approach shows good external volumetric generalization in an in-house dataset when tested with multi-view data (2. 76+-1. 89% compared to 3. 92+-3. 31%, P=. 002), showing the feasibility of exploiting non-annotated multi-view data through contrastive learning whilst providing flexibility at deployment in the event of missing views.

Contrastive Learning MRI segmentation

Prostate Age Gap (PAG): An MRI surrogate marker of aging for prostate cancer detection

no code implementations10 Aug 2023 Alvaro Fernandez-Quilez, Tobias Nordström, Fredrik Jäderling, Svein Reidar Kjosavik, Martin Eklund

Assessment: Chronological age was defined as the age of the participant at the time of the visit and used to train the deep learning model to predict the age of the patient.

Assessing gender fairness in EEG-based machine learning detection of Parkinson's disease: A multi-center study

1 code implementation11 Mar 2023 Anna Kurbatskaya, Alberto Jaramillo-Jimenez, John Fredy Ochoa-Gomez, Kolbjørn Brønnick, Alvaro Fernandez-Quilez

As the number of automatic tools based on machine learning (ML) and resting-state electroencephalography (rs-EEG) for Parkinson's disease (PD) detection keeps growing, the assessment of possible exacerbation of health disparities by means of fairness and bias analysis becomes more relevant.

EEG Electroencephalogram (EEG) +1

Machine Learning-Based Detection of Parkinson's Disease From Resting-State EEG: A Multi-Center Study

no code implementations2 Mar 2023 Anna Kurbatskaya, Alberto Jaramillo-Jimenez, John Fredy Ochoa-Gomez, Kolbjørn Brønnick, Alvaro Fernandez-Quilez

In particular, the power spectral density (PSD) of low-frequency bands ({\delta} and {\theta}) and high-frequency bands ({\alpha} and \b{eta}) has been shown to be significantly different in patients with PD as compared to subjects without PD (non-PD).

EEG Electroencephalogram (EEG) +1

3D Masked Modelling Advances Lesion Classification in Axial T2w Prostate MRI

no code implementations29 Dec 2022 Alvaro Fernandez-Quilez, Christoffer Gabrielsen Andersen, Trygve Eftestøl, Svein Reidar Kjosavik, Ketil Oppedal

Masked Image Modelling (MIM) has been shown to be an efficient self-supervised learning (SSL) pre-training paradigm when paired with transformer architectures and in the presence of a large amount of unlabelled natural images.

Lesion Classification Self-Supervised Learning

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