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Automated left atrial time-resolved segmentation in MRI long-axis cine images using active contours

Gonzales, Ricardo A. (author)
Lund University,Lunds universitet,Klinisk fysiologi, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Clinical Physiology (Lund),Section V,Department of Clinical Sciences, Lund,Faculty of Medicine
Seemann, Felicia (author)
Lund University,Lunds universitet,Klinisk fysiologi, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Clinical Physiology (Lund),Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,Yale University,Skåne University Hospital
Lamy, Jérôme (author)
Yale University
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Arvidsson, Per M. (author)
Lund University,Lunds universitet,Klinisk fysiologi, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Clinical Physiology (Lund),Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,Skåne University Hospital
Heiberg, Einar (author)
Lund University,Lunds universitet,Klinisk fysiologi, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,WCMM- Wallenberg center för molekylär medicinsk forskning,Clinical Physiology (Lund),Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,WCMM-Wallenberg Centre for Molecular Medicine,Skåne University Hospital
Murray, Victor (author)
Universidad de Ingeniería y Tecnología (UTEC),University of New Mexico
Peters, Dana C. (author)
Yale University
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 (creator_code:org_t)
2021-06-19
2021
English.
In: BMC Medical Imaging. - : Springer Science and Business Media LLC. - 1471-2342. ; 21:1
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Background: Segmentation of the left atrium (LA) is required to evaluate atrial size and function, which are important imaging biomarkers for a wide range of cardiovascular conditions, such as atrial fibrillation, stroke, and diastolic dysfunction. LA segmentations are currently being performed manually, which is time-consuming and observer-dependent. Methods: This study presents an automated image processing algorithm for time-resolved LA segmentation in cardiac magnetic resonance imaging (MRI) long-axis cine images of the 2-chamber (2ch) and 4-chamber (4ch) views using active contours. The proposed algorithm combines mitral valve tracking, automated threshold calculation, edge detection on a radially resampled image, edge tracking based on Dijkstra’s algorithm, and post-processing involving smoothing and interpolation. The algorithm was evaluated in 37 patients diagnosed mainly with paroxysmal atrial fibrillation. Segmentation accuracy was assessed using the Dice similarity coefficient (DSC) and Hausdorff distance (HD), with manual segmentations in all time frames as the reference standard. For inter-observer variability analysis, a second observer performed manual segmentations at end-diastole and end-systole on all subjects. Results: The proposed automated method achieved high performance in segmenting the LA in long-axis cine sequences, with a DSC of 0.96 for 2ch and 0.95 for 4ch, and an HD of 5.5 mm for 2ch and 6.4 mm for 4ch. The manual inter-observer variability analysis had an average DSC of 0.95 and an average HD of 4.9 mm. Conclusion: The proposed automated method achieved performance on par with human experts analyzing MRI images for evaluation of atrial size and function. [MediaObject not available: see fulltext.]

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Radiologi och bildbehandling (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Radiology, Nuclear Medicine and Medical Imaging (hsv//eng)

Keyword

Active contours
Cardiovascular imaging
Left atrium
Magnetic resonance imaging
Segmentation

Publication and Content Type

art (subject category)
ref (subject category)

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