Semi-Automatic Algorithms for Estimation and Tracking of AP-Diameter of the IVC in Ultrasound Images.
Ebrahim KaramiMohamed S ShehataAndrew SmithPublished in: Journal of imaging (2019)
Acutely ill patients presenting with conditions such as sepsis, trauma, and congestive heart failure require judicious resuscitation in order to achieve and maintain optimal circulating blood volume. Increasingly, emergency and critical care physicians are using portable ultrasound to approximate the temporal changes of the anterior-posterior (AP)-diameter of the inferior vena cava (IVC) in order to guide fluid administration or removal. This paper proposes semi-automatic active ellipse and rectangle algorithms capable of improved and quantified measurement of the AP-diameter. The proposed algorithms are compared to manual measurement and a previously published active circle model. Results demonstrate that the rectangle model outperforms both active circle and ellipse irrespective of IVC shape and closely approximates tedious expert assessment.
Keyphrases
- inferior vena cava
- deep learning
- machine learning
- pulmonary embolism
- heart failure
- transcription factor
- vena cava
- optic nerve
- convolutional neural network
- magnetic resonance imaging
- primary care
- cardiac arrest
- septic shock
- emergency department
- acute kidney injury
- healthcare
- intensive care unit
- systematic review
- optical coherence tomography
- contrast enhanced ultrasound
- ultrasound guided
- left ventricular
- atrial fibrillation
- computed tomography
- clinical evaluation