A Measure of Septum Shape Using Shortest Path Segmentation in Echocardiographic Images of LVAD Patients

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review


Patients waiting for heart transplantation due to a failing heart can get a left ventricular assist device (LVAD) implanted through open chest surgery. The device consists of a pump that pumps blood from the left ventricle into the aorta. To get the correct rotation speed of the pump, the physicians consider a number of measurements as well as a sequence of echocardiographic images. The important information obtained from the images is the shape of the inter-ventricular septum. For instance, if the septum bulges towards the left ventricle the speed is too high and it might harm the right ventricular function. To get a measure of the shape of the septum, which can be incorporated in a decision support system, we perform a segmentation of the septum using a shortest path method. To reduce user interaction, the user only needs to annotate two anchor points in the first frame. They mark the endpoints of the septum and they are tracked through the sequence with our tracking algorithm. After the segmentation the septum is divided into two regions, the one closest to the right ventricle and the one closest to the left ventricle, and the desired measure is the difference between the areas of these regions divided by the total septum area. The performance of the segmentation algorithm is acceptable and the obtained septum measure corresponds in most cases to the assessments from a physician.
Original languageEnglish
Title of host publicationPattern Recognition (ICPR), 2014 22nd International Conference on
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Number of pages6
Publication statusPublished - 2014
Event22nd International Conference on Pattern Recognition (ICPR 2014) - Stockholm, Sweden
Duration: 2014 Aug 242014 Aug 28
Conference number: 22

Publication series

ISSN (Print)1051-4651


Conference22nd International Conference on Pattern Recognition (ICPR 2014)

Subject classification (UKÄ)

  • Computer Vision and Robotics (Autonomous Systems)
  • Mathematics


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