title: Real-time aortic valve segmentation from transesophageal echocardiography sequence.
abstract: OBJECTIVE
  Geometric features of the aortic valve play an important role in many applications, such as the clinical diagnostics, shape modeling and image-guided cardiac interventions, especially for the transcatheter aortic valve implantation (TAVI) procedure. However, few works have been reported on the topic of aortic valve segmentation from transesophageal echocardiography (TEE) sequences. To obtain accurate segmentation results and further provide valid support for TAVI, this paper presents a real-time method for segmenting the aortic valve from intraoperative, short-axis view TEE sequences, using an improved probability estimation and continuous max-flow (CMF) approach.
  
  
  METHODS
  The proposed segmentation method includes two key stages: (1) In the probability estimation stage, five different prior frames spanning a cardiac circle are firstly selected with the aortic valve manually segmented by an expert. Then, the improved composite probability estimation (CPE) and single probability estimation (SPE) over the five prior frames are, respectively, constructed based on their radial average intensity and radial distance. (2) In the energy function construction stage, the similarity metric is calculated to find out the matching exponents between the current input TEE frame and the prior frames. The typical foreground and background intensities of prior images are therefore used to construct the corresponding energy function. Finally, the CMF approach, accelerated with a graphic processing unit (GPU), is employed to achieve the aortic valve contours in real time.
  
  
  RESULTS
  The evaluation study contained 30 sequences, with each containing 62-146 short-axis TEE frames. The results were compared with the manual segmentation (ground truth). The average symmetric contour distance (ASCD), dice metric (DM) and the reliability of the algorithm reached 0.85 ± 0.21 mm, 0.96 ± 0.01 and 0.90 (d = 0.95), respectively, and the computation time was 57.04 ± 8.98 ms per frame.
  
  
  CONCLUSIONS
  The experiment results reveal that the proposed method can achieve accurate and real-time segmentation of aortic valve from TEE sequence of short-axis view.
authors.affiliation: Department of Cardiosurgery, Ruijin Hospital, Shanghai, China.
authors.forename: Junfeng
authors.initials: J
authors.lastname: Cai
authors.forename: Xiahai
authors.initials: X
authors.lastname: Zhuang
authors.forename: Yuanyuan
authors.initials: Y
authors.lastname: Nie
authors.forename: Zhe
authors.initials: Z
authors.lastname: Luo
authors.forename: Lixu
authors.initials: L
authors.lastname: Gu
mesh_terms: D000465:Algorithms; D001021:Aortic Valve / Q000000981:diagnostic imaging* / Q000601:surgery*; D001024:Aortic Valve Stenosis / Q000601:surgery; D017548:Echocardiography, Transesophageal; D019918:Heart Valve Prosthesis Implantation / Q000379:methods*; D006801:Humans; D015203:Reproducibility of Results
references.citation: N Engl J Med. 2010 Oct 21;363(17):1597-607
references.pmid: 20961243
references.citation: Annu Int Conf IEEE Eng Med Biol Soc. 2013;2013:3311-4
references.pmid: 24110436
references.citation: IEEE Trans Med Imaging. 2009 Jun;28(6):881-93
references.pmid: 19150782
references.citation: IEEE Trans Med Imaging. 2002 Sep;21(9):1091-104
references.pmid: 12564877
references.citation: IEEE Trans Pattern Anal Mach Intell. 2004 Sep;26(9):1124-37
references.pmid: 15742889
references.citation: IEEE Trans Med Imaging. 2010 Sep;29(9):1676-87
references.pmid: 20562042
references.citation: Lancet. 2006 Sep 16;368(9540):1005-11
references.pmid: 16980116
references.citation: IEEE Trans Med Imaging. 2006 Aug;25(8):987-1010
references.pmid: 16894993
references.citation: IEEE Trans Med Imaging. 2009 Aug;28(8):1251-65
references.pmid: 19211338
references.citation: Med Image Anal. 2012 Jan;16(1):87-100
references.pmid: 21705264
references.citation: IEEE Trans Med Imaging. 2013 Nov;32(11):2152-65
references.pmid: 23912499
references.citation: J Endovasc Ther. 2004 Aug;11(4):503-10
references.pmid: 15298500
references.citation: IEEE Trans Med Imaging. 1996;15(1):25-38
references.pmid: 18215886
references.citation: Int J Comput Assist Radiol Surg. 2013 Jul;8(4):677-90
references.pmid: 23307285