no code implementations • 15 Mar 2024 • Chen Chen, Lei LI, Marcel Beetz, Abhirup Banerjee, Ramneek Gupta, Vicente Grau
We present a novel, lightweight dual-attention ECG network designed to capture complex ECG features essential for early HF risk prediction, despite the notable imbalance between low and high-risk groups.
no code implementations • 21 Dec 2023 • Hannah J. Smith, Blanca Rodriguez, Yuling Sang, Marcel Beetz, Robin Choudhury, Vicente Grau, Abhirup Banerjee
Smaller ventricles in females explain ~50% of shorter QRS durations than in males, and contribute to lower STJ amplitudes in females (also due to more superior and posterior position).
no code implementations • 20 Jul 2023 • Marcel Beetz, Abhirup Banerjee, Vicente Grau
Global single-valued biomarkers of cardiac function typically used in clinical practice, such as ejection fraction, provide limited insight on the true 3D cardiac deformation process and hence, limit the understanding of both healthy and pathological cardiac mechanics.
no code implementations • 20 Jul 2023 • Marcel Beetz, Abhirup Banerjee, Vicente Grau
In this work, we present the multi-objective point cloud autoencoder as a novel geometric deep learning approach for explainable infarction prediction, based on multi-class 3D point cloud representations of cardiac anatomy and function.
no code implementations • 17 Jul 2023 • Marcel Beetz, Abhirup Banerjee, Julius Ossenberg-Engels, Vicente Grau
Cine magnetic resonance imaging (MRI) is the current gold standard for the assessment of cardiac anatomy and function.
no code implementations • 14 Jul 2023 • Marcel Beetz, Yilong Yang, Abhirup Banerjee, Lei LI, Vicente Grau
Myocardial infarction (MI) is one of the most prevalent cardiovascular diseases with associated clinical decision-making typically based on single-valued imaging biomarkers.
no code implementations • 10 Jul 2023 • Lei LI, Julia Camps, Zhinuo, Wang, Abhirup Banerjee, Marcel Beetz, Blanca Rodriguez, Vicente Grau
In this work, we investigate the feasibility of inferring myocardial tissue properties from the electrocardiogram (ECG) within a CDT platform.
1 code implementation • 28 Apr 2023 • Yuhao Huang, Xin Yang, Lian Liu, Han Zhou, Ao Chang, Xinrui Zhou, Rusi Chen, Junxuan Yu, Jiongquan Chen, Chaoyu Chen, Sijing Liu, Haozhe Chi, Xindi Hu, Kejuan Yue, Lei LI, Vicente Grau, Deng-Ping Fan, Fajin Dong, Dong Ni
To fully validate SAM's performance on medical data, we collected and sorted 53 open-source datasets and built a large medical segmentation dataset with 18 modalities, 84 objects, 125 object-modality paired targets, 1050K 2D images, and 6033K masks.
no code implementations • 4 Apr 2023 • Lei LI, Julia Camps, Zhinuo, Wang, Abhirup Banerjee, Blanca Rodriguez, Vicente Grau
However, the influence of various MI properties on the QRS is not intuitively predictable. In this work, we have systematically investigated the effects of 17 post-MI scenarios, varying the location, size, transmural extent, and conductive level of scarring and border zone area, on the forward-calculated QRS.
no code implementations • 26 Aug 2022 • Lei LI, Wangbin Ding, Liqun Huang, Xiahai Zhuang, Vicente Grau
Multi-modality cardiac imaging plays a key role in the management of patients with cardiovascular diseases.
no code implementations • 8 Aug 2022 • Lei LI, Julia Camps, Abhirup Banerjee, Marcel Beetz, Blanca Rodriguez, Vicente Grau
Cardiac digital twins can provide non-invasive characterizations of cardiac functions for individual patients, and therefore are promising for the patient-specific diagnosis and therapy stratification.
no code implementations • 28 Oct 2020 • Julia Camps, Brodie Lawson, Christopher Drovandi, Ana Minchole, Zhinuo Jenny Wang, Vicente Grau, Kevin Burrage, Blanca Rodriguez
We demonstrate results from our inference method on a cohort of twenty virtual subjects with cardiac volumes ranging from 74 cm3 to 171 cm3 and considering low versus high resolution for the endocardial discretisation (which determines possible locations of the earliest activation sites).
no code implementations • 2 Mar 2020 • Anirudh Chandrashekar, Ashok Handa, Natesh Shivakumar, Pierfrancesco Lapolla, Vicente Grau, Regent Lee
This pipeline is able to differentiate between visually incoherent soft tissue regions in non-contrast CT images.
no code implementations • 9 Feb 2020 • Anirudh Chandrashekar, Ashok Handa, Natesh Shivakumar, Pierfrancesco Lapolla, Vicente Grau, Regent Lee
Subsequent implementation of this network architecture within the aortic segmentation pipeline from both contrast-enhanced CTA and non-contrast CT images has allowed for accurate and efficient extraction of the entire aortic volume.
1 code implementation • 16 Sep 2019 • Hoileong Lee, Tahreema Matin, Fergus Gleeson, Vicente Grau
We refer to the network as Pulmonary Lobe Segmentation Network (PLS-Net), which is designed to efficiently exploit 3D spatial and contextual information from high-resolution volumetric CT images for effective volume-to-volume learning and inference.
no code implementations • 26 May 2017 • Russell Bates, Benjamin Irving, Bostjan Markelc, Jakob Kaeppler, Ruth Muschel, Vicente Grau, Julia A. Schnabel
Vasculature is known to be of key biological significance, especially in the study of cancer.