Related papers: Improved Visualisation of Patient-Specific Heart S…
Medical imaging phantoms are widely used for validation and verification of imaging systems and algorithms in surgical guidance and radiation oncology procedures. Especially, for the performance evaluation of new algorithms in the field of…
3D printing has been widely adopted for clinical decision making and interventional planning of Congenital heart disease (CHD), while whole heart and great vessel segmentation is the most significant but time-consuming step in the model…
Purpose: Anthropomorphic phantoms can be used in radiotherapy to confirm dose distributions. In this work, a prototype phantom with a deformable chest wall was created based on real human. Methods: A technique similar to 3-dimensional…
Myocardial infarction (MI) is one of the most prevalent cardiovascular diseases with associated clinical decision-making typically based on single-valued imaging biomarkers. However, such metrics only approximate the complex 3D structure…
Knowledge of appropriate local fiber architecture is necessary to simulate patient-specific electromechanics in the human heart. However, it is not yet possible to reliably measure in-vivo fiber directions, especially in human atria. Thus,…
The AstroMed project at Harvard University's Initiative in Innovative Computing (IIC) is working on improved visualization and data sharing solutions applicable to the fields of both astronomy and medicine. The current focus is on the…
Electroanatomical mapping is a technique used in cardiology to create a detailed 3D map of the electrical activity in the heart. It is useful for diagnosis, treatment planning and real time guidance in cardiac ablation procedures to treat…
Intracardiac flow patterns are shaped by the coupled motion of the cardiac chambers and heart valves and provide important information about cardiac function. However, clinical flow imaging remains limited by exam times, noise, resolution,…
Cardiac segmentation of atriums, ventricles, and myocardium in computed tomography (CT) images is an important first-line task for presymptomatic cardiovascular disease diagnosis. In several recent studies, deep learning models have shown…
Alterations in the geometry and function of the heart define well-established causes of cardiovascular disease. However, current approaches to the diagnosis of cardiovascular diseases often rely on subjective human assessment as well as…
We present the first geometric deep learning framework based on point cloud representation for 3D four-chamber cardiac reconstruction from cine MRI data. This work addresses a long-standing limitation in conventional cine MRI, which…
Myocardial perfusion imaging using SPECT is widely utilized to diagnose coronary artery diseases, but image quality can be negatively affected in low-dose and few-view acquisition settings. Although various deep learning methods have been…
Mesh reconstruction of the cardiac anatomy from medical images is useful for shape and motion measurements and biophysics simulations to facilitate the assessment of cardiac function and health. However, 3D medical images are often acquired…
Unsafe surgical care is a critical health concern, often linked to limitations in surgeon experience, skills, and situational awareness. Integrating patient-specific 3D models into the surgical field can enhance visualization, provide…
Image-based computer simulation of cardiac function can be used to probe the mechanisms of (patho)physiology, and guide diagnosis and personalized treatment of cardiac diseases. This paradigm requires constructing simulation-ready meshes of…
As diffusion tensor imaging (DTI) gains popularity in cardiac imaging due to its unique ability to non-invasively assess the cardiac microstructure, deep learning-based Artificial Intelligence is becoming a crucial tool in mitigating some…
Myocardial infarction causes myocardium thinning, fibrosis, and progressive heart failure. Engineered human myocardium (EHM) is tested clinically as a first-in-class product for sustainable remuscularization in patients with advanced heart…
Owing to their intricate variable density architecture, and as a principal site of star formation, molecular clouds represent one of the most functionally significant, yet least understood features of our universe. To unravel the intrinsic…
The perfect alignment of 3D echocardiographic images captured from various angles has improved image quality and broadened the field of view. This study proposes an accelerated sequential Monte Carlo (SMC) algorithm for 3D-3D rigid…
Accurate 3D aortic construction is crucial for clinical diagnosis, preoperative planning, and computational fluid dynamics (CFD) simulations, as it enables the estimation of critical hemodynamic parameters such as blood flow velocity,…