3D Hermite Transform Optical Flow Estimation inLeft Ventricle CT Sequences.
Carlos MiraErnesto Moya-AlborBoris Escalante-RamirezJimena OlveresJorge BrievaEnrique VallejoPublished in: Sensors (Basel, Switzerland) (2020)
Heart diseases are the most important causes of death in the world and over the years, thestudy of cardiac movement has been carried out mainly in two dimensions, however, it is important toconsider that the deformations due to the movement of the heart occur in a three-dimensional space.The 3D + t analysis allows to describe most of the motions of the heart, for example, the twistingmotion that takes place on every beat cycle that allows us identifying abnormalities of the heartwalls. Therefore, it is necessary to develop algorithms that help specialists understand the cardiacmovement. In this work, we developed a new approach to determine the cardiac movement inthree dimensions using a differential optical flow approach in which we use the steered Hermitetransform (SHT) which allows us to decompose cardiac volumes taking advantage of it as a model ofthe human vision system (HVS). Our proposal was tested in complete cardiac computed tomography(CT) volumes ( 3D + t), as well as its respective left ventricular segmentation. The robustness tonoise was tested with good results. The evaluation of the results was carried out through errors inforwarding reconstruction, from the volume at time t to time t + 1 using the optical flow obtained(interpolation errors). The parameters were tuned extensively. In the case of the 2D algorithm, theinterpolation errors and normalized interpolation errors are very close and below the values reportedin ground truth flows. In the case of the 3D algorithm, the results were compared with another similarmethod in 3D and the interpolation errors remained below 0.1. These results of interpolation errorsfor complete cardiac volumes and the left ventricle are shown graphically for clarity. Finally, a seriesof graphs are observed where the characteristic of contraction and dilation of the left ventricle isevident through the representation of the 3D optical flow.
Keyphrases
- left ventricular
- computed tomography
- heart failure
- patient safety
- machine learning
- deep learning
- mitral valve
- high resolution
- high speed
- adverse drug
- pulmonary hypertension
- endothelial cells
- positron emission tomography
- acute myocardial infarction
- magnetic resonance imaging
- hypertrophic cardiomyopathy
- dual energy
- image quality
- pulmonary artery
- atrial fibrillation
- left atrial
- multidrug resistant
- emergency department
- aortic stenosis
- magnetic resonance
- congenital heart disease