Catheter segmentation in three-dimensional ultrasound images by feature fusion and model fitting

Abstract

Ultrasound (US) has been increasingly used during interventions, such as cardiac catheterization. To accurately identify the catheter inside US images, extra training for physicians and sonographers is needed. As a consequence, automated segmentation of the catheter in US images and optimized presentation viewing to the physician can be beneficial to accelerate the efficiency and safety of interventions and improve their outcome. For cardiac catheterization, a three-dimensional (3-D) US image is potentially attractive because of no radiation modality and richer spatial information. However, due to a limited spatial resolution of 3-D cardiac US and complex anatomical structures inside the heart, image-based catheter segmentation is challenging. We propose a cardiac catheter segmentation method in 3-D US data through image processing techniques. Our method first applies a voxel-based classification through newly designed multiscale and multidefinition features, which provide a robust catheter voxel segmentation in 3-D US. Second, a modified catheter model fitting is applied to segment the curved catheter in 3-D US images. The proposed method is validated with extensive experiments, using different in-vitro, ex-vivo, and in-vivo datasets. The proposed method can segment the catheter within an average tip-point error that is smaller than the catheter diameter (1.9 mm) in the volumetric images. Based on automated catheter segmentation and combined with optimal viewing, physicians do not have to interpret US images and can focus on the procedure itself to improve the quality of cardiac intervention.

Medical Instrument Detection in Ultrasound-Guided Interventions: A Review

“…4). To further exploit complex anatomical information in 3D US for catheter segmentation in cardiac catheterization, Yang et al proposed multi-scale and multidefinition features for supervised learning classifiers, which demonstrated a better discriminating information extraction than techniques solely based on Gabor features [60], [61]. The segmented instrument was fitted by a more complex Sparse-Plus-Dense RANSAC algorithm to fit the curvature instrument in the cardiac chambers.…”

“…Moreover, due to complex anatomical structures in the heart chambers, sonographers need more time to localize the less obvious catheter (compared to the metal needle) in 3D volumetric data by a slice-by-slice tuning procedure, which is time-consuming and complicates the operation. Nevertheless, 3D ultrasound is attractive for catheterizations because of its radiation-free nature and easy-to-use properties, and its richer offering of spatial information for tissues [61]. As a result, it is a promising choice to support or replace current Xray imaging for cardiac interventions.…”

“…To detect the catheter in 3D US images, several solutions were proposed [38], [61], [85], which employed different methods as reviewed in Section II. However, there are still several challenges that need to be addressed in the future work: (1) US-guided catheterization is not widely accepted for clinical usage so that expert knowledge is limited by experience.…”

“…Needle biopsy/anesthesia/therapy ex-vivo Kaya et al [41] 2015 2D+t Needle biopsy/drug delivery in-vitro Pourtaherian et al [37] 2016 3D Needle anesthesia/ablation ex-vivo Beigi et al [45] 2016 2D+t Needle biopsy/nerve block/anesthesias in-vitro/in-vivo Mwikirize et al [43] 2016 2D Needle biopsy/ablation/anesthesia ex-vivo Beigi et al [48] 2016 2D+t Needle biopsy/nerve block/anesthesia in-vivo Kaya et al [46] 2016 2D+t Needle biopsy/drug delivery in-vitro Daoud et al [49] 2018 3D Needle intervention ex-vivo Daoud et al [24] 2018 2D Needle intervention ex-vivo Agarwal et al [35] 2019 2D+t Anesthesia/biopsy/brachytherapy in-vitro Needle biopsy/ablation/anesthesia ex-vivo Yang et al [61] 2019 3D Cardiac catheterization in-vitro/ex-vivo/in-vivo Yang et al [70] 2019 3D Cardiac catheterization ex-vivo Yang et al [82] 2019 3D Cardiac catheterization ex-vivo Yang et al [83] 2019 3D Cardiac catheterization ex-vivo Mwikirize et al [89] 2019 2D+t Needle biopsy/anesthesia in-vitro/ex-vivo Mwikirize et al [88] 2019 2D+t Needle biopsy/anesthesia ex-vivo Arif et al [87] 2019 3D Needle biopsy in-vitro/in-vivo Yang et al [85] 2019 3D Cardiac catheterization ex-vivo/in-vivo Min et al [76] 2020 3D Cardiac catheterization ex-vivo Rodgers et al [80] 2020 2D/3D Interstitial gynecologic brachytherapy in-vitro/in-vivo Zhang et al [68], [67] 2020 3D prostate brachytherapy in-vivo Zhang et al [86] 2020 3D Prostate brachytherapy in-vivo Zhang et al [90] 2020 3D Prostate brachytherapy in-vivo Lee et al [79] 2020 2D Needle biopsy in-vivo With the above summaries, there are remaining some challenges and limitations for this area, despite the current methods obtain satisfactory results. We discuss these challenges below.…”

Catheter localization in 3D ultrasound using voxel-of-interest-based ConvNets for cardiac intervention

“…The classified volume may include some outliers, which are generated from the blurry tissue boundaries or catheter-like anatomical structures. To robustly localize the catheter, we employ our previously designed SPD-RANSAC method to fit a pre-defined catheter model [ 12 ]. A curved cylinder models the catheter with a fixed radius, which is set to be three voxels in this paper.…”