214 research outputs found
Self-supervised motion descriptor for cardiac phase detection in 4D CMR based on discrete vector field estimations
Cardiac magnetic resonance (CMR) sequences visualise the cardiac function
voxel-wise over time. Simultaneously, deep learning-based deformable image
registration is able to estimate discrete vector fields which warp one time
step of a CMR sequence to the following in a self-supervised manner. However,
despite the rich source of information included in these 3D+t vector fields, a
standardised interpretation is challenging and the clinical applications remain
limited so far. In this work, we show how to efficiently use a deformable
vector field to describe the underlying dynamic process of a cardiac cycle in
form of a derived 1D motion descriptor. Additionally, based on the expected
cardiovascular physiological properties of a contracting or relaxing ventricle,
we define a set of rules that enables the identification of five cardiovascular
phases including the end-systole (ES) and end-diastole (ED) without the usage
of labels. We evaluate the plausibility of the motion descriptor on two
challenging multi-disease, -center, -scanner short-axis CMR datasets. First, by
reporting quantitative measures such as the periodic frame difference for the
extracted phases. Second, by comparing qualitatively the general pattern when
we temporally resample and align the motion descriptors of all instances across
both datasets. The average periodic frame difference for the ED, ES key phases
of our approach is , which is slightly better
than the inter-observer variability (, ) and the
supervised baseline method (, ). Code and labels
will be made available on our GitHub repository.
https://github.com/Cardio-AI/cmr-phase-detectionComment: accepted for the STACOM2022 workshop @ MICCAI202
Cardiovascular magnetic resonance:Diagnostic utility and specific considerations in the pediatric population
Cardiovascular magnetic resonance is a non-invasive imaging modality which is emerging as important tool for the investigation and management of pediatric cardiovascular disease. In this review we describe the key technical and practical differences between scanning children and adults, and highlight some important considerations that must be taken into account for this patient population. Using case examples commonly seen in clinical practice, we discuss the important clinical applications of cardiovascular magnetic resonance, and briefly highlight key future developments in this field
- …