VESCL: an open source 2D vessel contouring library
Name
11548_2024_3212_ReferencePDF.pdf
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Author(s)
Frisken, S. F.
Haouchine, N.
Chlorogiannis, D. D.
Gopalakrishnan, V.
Cafaro, A.
Wells, W. T.
Golby, A. J.
Du, R.
Date Issued
June 16, 2024
Journal
International Journal of Computer Assisted Radiology and Surgery
Publisher
Springer International Publishing
Citation
Frisken, S.F., Haouchine, N., Chlorogiannis, D.D. et al. VESCL: an open source 2D vessel contouring library. Int J CARS 19, 1627–1636 (2024).
Version
Author's final manuscript
Abstract
Purpose VESCL (pronounced ‘vessel’) is a novel vessel contouring library for computer-assisted 2D vessel contouring and segmentation. VESCL facilitates manual vessel segmentation in 2D medical images to generate gold-standard datasets for training, testing, and validating automatic vessel segmentation. Methods VESCL is an open-source C++ library designed for easy integration into medical image processing systems. VESCL provides an intuitive interface for drawing variable-width parametric curves along vessels in 2D images. It includes highly optimized localized filtering to automatically fit drawn curves to the nearest vessel centerline and automatically determine the varying vessel width along each curve. To support a variety of segmentation paradigms, VESCL can export multiple segmentation representations including binary segmentations, occupancy maps, and distance fields. Results VESCL provides sub-pixel resolution for vessel centerlines and vessel widths. It is optimized to segment small vessels with single- or sub-pixel widths that are visible to the human eye but hard to segment automatically via conventional filters. When tested on neurovascular digital subtraction angiography (DSA), VESCL’s intuitive hand-drawn input with automatic curve fitting increased the speed of fully manual segmentation by 22× over conventional methods and by 3× over the best publicly available computer-assisted manual segmentation method. Accuracy was shown to be within the range of inter-operator variability of gold standard manually segmented data from a publicly available dataset of neurovascular DSA images as measured using Dice scores. Preliminary tests showed similar improvements for segmenting DSA of coronary arteries and RGB images of retinal arteries. Conclusion VESCL is an open-source C++ library for contouring vessels in 2D images which can be used to reduce the tedious, labor-intensive process of manually generating gold-standard segmentations for training, testing, and comparing automatic segmentation methods.
MIT Department
Harvard University--MIT Division of Health Sciences and Technology
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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DOI of Published Version
https://doi.org/10.1007/s11548-024-03212-0
