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Automated Coronary Artery Tracking with a Voronoi-Based 3D Centerline Extraction Algorithm

Dalvit Carvalho da Silva, Rodrigo ; Soltanzadeh, Ramin ; Figley, Chase R

Journal of imaging, 2023-12, Vol.9 (12), p.268 [Periódico revisado por pares]

Switzerland: MDPI AG

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Título:
Automated Coronary Artery Tracking with a Voronoi-Based 3D Centerline Extraction Algorithm
Autor: Dalvit Carvalho da Silva, Rodrigo ; Soltanzadeh, Ramin ; Figley, Chase R
Assuntos: Accuracy ; Algorithms ; Annotations ; Automation ; Cardiovascular disease ; centerline ; Computed tomography ; Computer-aided medical diagnosis ; coronary artery ; Coronary artery disease ; Coronary heart disease ; Coronary vessels ; Datasets ; Diagnosis ; Image processing ; Medical imaging ; Medical imaging equipment ; Methods ; MICCAI coronary artery tracking challenge ; Rotterdam coronary artery algorithm evaluation framework ; Technology application ; Tracking ; Training ; Voronoi diagram ; Voronoi graphs
É parte de: Journal of imaging, 2023-12, Vol.9 (12), p.268
Notas: ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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Descrição: Coronary artery disease is one of the leading causes of death worldwide, and medical imaging methods such as coronary artery computed tomography are vitally important in its detection. More recently, various computational approaches have been proposed to automatically extract important artery coronary features (e.g., vessel centerlines, cross-sectional areas along vessel branches, etc.) that may ultimately be able to assist with more accurate and timely diagnoses. The current study therefore validated and benchmarked a recently developed automated 3D centerline extraction method for coronary artery centerline tracking using synthetically segmented coronary artery models based on the widely used Rotterdam Coronary Artery Algorithm Evaluation Framework (RCAAEF) training dataset. Based on standard accuracy metrics and the ground truth centerlines of all 32 coronary vessel branches in the RCAAEF training dataset, this 3D divide and conquer Voronoi diagram method performed exceptionally well, achieving an average overlap accuracy (OV) of 99.97%, overlap until first error (OF) of 100%, overlap of the clinically relevant portion of the vessel (OT) of 99.98%, and an average error distance inside the vessels (AI) of only 0.13 mm. Accuracy was also found to be exceptionally for all four coronary artery sub-types, with average OV values of 99.99% for right coronary arteries, 100% for left anterior descending arteries, 99.96% for left circumflex arteries, and 100% for large side-branch vessels. These results validate that the proposed method can be employed to quickly, accurately, and automatically extract 3D centerlines from segmented coronary arteries, and indicate that it is likely worthy of further exploration given the importance of this topic.
Editor: Switzerland: MDPI AG
Idioma: Inglês

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Automated Coronary Artery Tracking with a Voronoi-Based 3D Centerline Extraction Algorithm

Dalvit Carvalho da Silva, Rodrigo ; Soltanzadeh, Ramin ; Figley, Chase R

Switzerland: MDPI AG

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