Maanas Pavuluri
Research Mentor(s): David Nordsletten
Mentor Department: Biomedical Engineering
Authors: Javiera Vallejos, Maanas Pavuluri, David Nordsletten
Session: Session 5 (2:00pm – 2:50pm)
Presentation Type: Poster 77
Abstract
Creating computational models of cardio biomechanics is a promising tool for understanding cardiovascular disease and developing effective treatment strategies. These types of models are created from medical images, such as computational tomography (CT) or magnetic resonance images (MRI). CT scans provide high spatial resolution and anatomical detail, but expose patients to ionizing radiation, while MRIs are safer in terms of radiation exposure but suffer from lower resolution and longer acquisition times. However, creating accurate patient-specific models of the heart from MRI is challenging due to the low 3D resolution and technical factors that lead to misalignment between individual images. Not fixing these misalignments will lead to poor anatomical models of the heart that will impact the reliability of simulations. This project aims to first characterize and quantify the errors produced by the misalignment in MRIs by generating synthetic scans from CT data that can reproduce misalignment and resolution issues. Then, we will use this framework to implement an optimized pipeline capable of detecting and correcting these misalignments to enhance model accuracy. Our pipeline begins with a NIfTI file that is generated from CT scans. A synthetic MRI is produced based on this data, which is then compared to the original CT scan to evaluate the effectiveness of the alignment algorithms. By simulating and analyzing different misalignment scenarios, we assess how these discrepancies propagate through the pipeline and affect the final synthetic MRI output. This approach allows for comprehensive testing of alignment strategies under varying conditions.
