Search Results for author: Reza Razavi

Found 21 papers, 3 papers with code

Uncertainty Aware Training to Improve Deep Learning Model Calibration for Classification of Cardiac MR Images

no code implementations29 Aug 2023 Tareen Dawood, Chen Chen, Baldeep S. Sidhua, Bram Ruijsink, Justin Goulda, Bradley Porter, Mark K. Elliott, Vishal Mehta, Christopher A. Rinaldi, Esther Puyol-Anton, Reza Razavi, Andrew P. King

The best-performing model in terms of both classification accuracy and the most common calibration measure, expected calibration error (ECE) was the Confidence Weight method, a novel approach that weights the loss of samples to explicitly penalise confident incorrect predictions.

Feature-Conditioned Cascaded Video Diffusion Models for Precise Echocardiogram Synthesis

no code implementations22 Mar 2023 Hadrien Reynaud, Mengyun Qiao, Mischa Dombrowski, Thomas Day, Reza Razavi, Alberto Gomez, Paul Leeson, Bernhard Kainz

So far, video generation has only been possible by providing input data that is as rich as the output data, e. g., image sequence plus conditioning in, video out.

Image Generation Video Generation

Addressing Deep Learning Model Calibration Using Evidential Neural Networks and Uncertainty-Aware Training

no code implementations30 Jan 2023 Tareen Dawood, Emily Chan, Reza Razavi, Andrew P. King, Esther Puyol-Anton

However, in our complex artefact detection task, we saw an improvement in calibration for both a low and higher-capacity model when implementing both the ENN and uncertainty-aware training together, indicating that this approach can offer a promising way to improve calibration in such settings.


Automated Quality Controlled Analysis of 2D Phase Contrast Cardiovascular Magnetic Resonance Imaging

no code implementations28 Sep 2022 Emily Chan, Ciaran O'Hanlon, Carlota Asegurado Marquez, Marwenie Petalcorin, Jorge Mariscal-Harana, Haotian Gu, Raymond J. Kim, Robert M. Judd, Phil Chowienczyk, Julia A. Schnabel, Reza Razavi, Andrew P. King, Bram Ruijsink, Esther Puyol-Antón

Flow analysis carried out using phase contrast cardiac magnetic resonance imaging (PC-CMR) enables the quantification of important parameters that are used in the assessment of cardiovascular function.

An AI tool for automated analysis of large-scale unstructured clinical cine CMR databases

no code implementations15 Jun 2022 Jorge Mariscal-Harana, Clint Asher, Vittoria Vergani, Maleeha Rizvi, Louise Keehn, Raymond J. Kim, Robert M. Judd, Steffen E. Petersen, Reza Razavi, Andrew King, Bram Ruijsink, Esther Puyol-Antón

We show that our proposed tool, which combines image pre-processing steps, a domain-generalisable AI algorithm trained on a large-scale multi-domain CMR dataset and quality control steps, allows robust analysis of (clinical or research) databases from multiple centres, vendors, and cardiac diseases.

AI-enabled Assessment of Cardiac Systolic and Diastolic Function from Echocardiography

1 code implementation21 Mar 2022 Esther Puyol-Antón, Bram Ruijsink, Baldeep S. Sidhu, Justin Gould, Bradley Porter, Mark K. Elliott, Vishal Mehta, Haotian Gu, Miguel Xochicale, Alberto Gomez, Christopher A. Rinaldi, Martin Cowie, Phil Chowienczyk, Reza Razavi, Andrew P. King

In this work we propose for the first time an AI approach for deriving advanced biomarkers of systolic and diastolic LV function from 2-D echocardiography based on segmentations of the full cardiac cycle.


Uncertainty-Aware Training for Cardiac Resynchronisation Therapy Response Prediction

no code implementations22 Sep 2021 Tareen Dawood, Chen Chen, Robin Andlauer, Baldeep S. Sidhu, Bram Ruijsink, Justin Gould, Bradley Porter, Mark Elliott, Vishal Mehta, C. Aldo Rinaldi, Esther Puyol-Antón, Reza Razavi, Andrew P. King

Evaluation of predictive deep learning (DL) models beyond conventional performance metrics has become increasingly important for applications in sensitive environments like healthcare.

Improved AI-based segmentation of apical and basal slices from clinical cine CMR

no code implementations20 Sep 2021 Jorge Mariscal-Harana, Naomi Kifle, Reza Razavi, Andrew P. King, Bram Ruijsink, Esther Puyol-Antón

Using manual segmentations as a reference, CMR slices were assigned to one of four regions: non-cardiac, base, middle, and apex.

Can non-specialists provide high quality gold standard labels in challenging modalities?

no code implementations30 Jul 2021 Samuel Budd, Thomas Day, John Simpson, Karen Lloyd, Jacqueline Matthew, Emily Skelton, Reza Razavi, Bernhard Kainz

We study the time and cost implications of using novice annotators, the raw performance of novice annotators compared to gold-standard expert annotators, and the downstream effects on a trained Deep Learning segmentation model's performance for detecting a specific congenital heart disease (hypoplastic left heart syndrome) in fetal ultrasound imaging.

Fairness in Cardiac MR Image Analysis: An Investigation of Bias Due to Data Imbalance in Deep Learning Based Segmentation

no code implementations23 Jun 2021 Esther Puyol-Anton, Bram Ruijsink, Stefan K. Piechnik, Stefan Neubauer, Steffen E. Petersen, Reza Razavi, Andrew P. King

The subject of "fairness" in artificial intelligence (AI) refers to assessing AI algorithms for potential bias based on demographic characteristics such as race and gender, and the development of algorithms to address this bias.

Fairness Meta-Learning

Automatic Detection of B-lines in Lung Ultrasound Videos From Severe Dengue Patients

no code implementations1 Feb 2021 Hamideh Kerdegari, Phung Tran Huy Nhat, Angela McBride, VITAL Consortium, Reza Razavi, Nguyen Van Hao, Louise Thwaites, Sophie Yacoub, Alberto Gomez

Lung ultrasound (LUS) imaging is used to assess lung abnormalities, including the presence of B-line artefacts due to fluid leakage into the lungs caused by a variety of diseases.

Quality-aware semi-supervised learning for CMR segmentation

no code implementations1 Sep 2020 Bram Ruijsink, Esther Puyol-Anton, Ye Li, Wenja Bai, Eric Kerfoot, Reza Razavi, Andrew P. King

SemiQCSeg can be an efficient approach for training segmentation networks for medical image data when labelled datasets are scarce.

Data Augmentation Image Segmentation +2

Assessing the Impact of Blood Pressure on Cardiac Function Using Interpretable Biomarkers and Variational Autoencoders

no code implementations13 Aug 2019 Esther Puyol-Antón, Bram Ruijsink, James R. Clough, Ilkay Oksuz, Daniel Rueckert, Reza Razavi, Andrew P. King

Maintaining good cardiac function for as long as possible is a major concern for healthcare systems worldwide and there is much interest in learning more about the impact of different risk factors on cardiac health.

Fetal whole-heart 4D imaging using motion-corrected multi-planar real-time MRI

3 code implementations5 Dec 2018 Joshua FP van Amerom, David FA Lloyd, Maria Deprez, Anthony N. Price, Shaihan J. Malik, Kuberan Pushparajah, Milou PM van Poppel, Mary A. Rutherford, Reza Razavi, Joseph V. Hajnal

Expert evaluation suggested the reconstructed volumes can be used for comprehensive assessment of the fetal heart, either as an adjunct to ultrasound or in combination with other MRI techniques.

Medical Physics

Mind the gap: quantification of incomplete ablation patterns after pulmonary vein isolation using minimum path search

1 code implementation17 Jun 2018 Marta Nuñez-Garcia, Oscar Camara, Mark D. O'Neill, Reza Razavi, Henry Chubb, Constantine Butakoff

Pulmonary vein isolation (PVI) is a common procedure for the treatment of atrial fibrillation (AF).

Computational Engineering, Finance, and Science

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