title: Automatic 3D modelling of human diaphragm from lung MDCT images.
abstract: OBJECTIVE
  The thoracic diaphragm separates the thorax and abdomen cavity and also performs an important function in respiration. An automatic algorithm to model the human full diaphragm from multi-detector computed tomography (MDCT) images has been developed and tested.
  
  
  METHODS
  The modelling algorithm comprises these steps: (i) diaphragm top boundary estimation (ii) diaphragm side boundary estimation and (iii) full diaphragm modelling in 3D. Diaphragm top boundary is estimated based on lungs' diaphragmatic surfaces with three different methods including: linear interpolation and fitting fourth and fifth degree polynomial surfaces. Diaphragm side boundary is assumed as the inner surfaces of the lower ribs, spinal column and costal cartilages, estimated via interpolation. As the last step, the full diaphragm is modelled by employing 3D active contours that are initiated from a predefined mesh and expand towards the estimated boundaries of the diaphragm. The proposed algorithm was tested on MDCT datasets from 15 patients, and the result were compared to reference masks provided by an experienced radiologist.
  
  
  RESULTS
  Based on quantitative evaluations, the accuracy of the algorithm highly depends on the diaphragm top surface estimation, e.g., the proposed algorithm failed on two datasets, both with enlarged pericardial fat pad that cuts off the left lung from the diaphragm. The proposed algorithm was tested on the remaining 13 datasets in which lungs' lower surfaces have normal contact with the diaphragm. To perform quantitative evaluations, four slices per dataset including an axial, mid-coronal and one-fourth of the sagittal planes from left and right, were compared to the ground truth. Hausdorff distance and mean distance to the closest point were measured to be 11.61 and 3.46 mm respectively, when the diaphragm top surface is modelled by a fourth degree polynomial surface.
  
  
  CONCLUSIONS
  Human full diaphragm can be automatically modelled with 3D active contours bounded by the lower surfaces of the lungs and inner surfaces of the lower ribs, spinal column and costal cartilages.
authors.affiliation: School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, 2052, Australia. bpazoki@cse.unsw.edu.au.
authors.forename: Banafsheh
authors.initials: B
authors.lastname: Pazokifard
authors.affiliation: School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, 2052, Australia.
authors.forename: Arcot
authors.initials: A
authors.lastname: Sowmya
authors.affiliation: Department of Medical Imaging, Prince of Wales Clinical School, University of New South Wales, Sydney, NSW, 2052, Australia.
authors.forename: Daniel
authors.initials: D
authors.lastname: Moses
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D066186:Costal Cartilage / Q000000981:diagnostic imaging; D003964:Diaphragm / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional; D008168:Lung / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D008953:Models, Anatomic; D061330:Multidetector Computed Tomography; D012272:Ribs / Q000000981:diagnostic imaging; D013131:Spine / Q000000981:diagnostic imaging; D055815:Young Adult
keywords: 3D; Full diaphragm; Fully automatic; MDCT; Modelling