M. Abayazid, P. Moreira, Navid Shahriari, Anastasios Zompas, S. Misra
{"title":"Three-Dimensional Needle Steering Using Automated Breast Volume Scanner (ABVS)","authors":"M. Abayazid, P. Moreira, Navid Shahriari, Anastasios Zompas, S. Misra","doi":"10.1142/S2424905X16400055","DOIUrl":null,"url":null,"abstract":"Robot-assisted and ultrasound-guided needle insertion systems assist in achieving high targeting accuracy for different applications. In this paper, we introduce the use of Automated Breast Volume Scanner (ABVS) for scanning different soft tissue phantoms. The ABVS is a commercial ultrasound transducer used for clinical breast scanning. A preoperative scan is performed for three-dimensional (3D) target localization and shape reconstruction. The ultrasound transducer is also adapted to be used for tracking the needle tip during steering toward the localized targets. The system uses the tracked needle tip position as a feedback to the needle control algorithm. The bevel-tipped flexible needle is steered under ABVS guidance toward a target while avoiding an obstacle embedded in soft tissue phantom. We present experimental results for 3D reconstruction of different convex and non-convex objects with different sizes. Mean Absolute Distance (MAD) and Dice’s coefficient methods are used to evaluate the 3D shape reconstruction algorithm. The results show that the mean MAD values are 0.30±0.13mm and 0.34±0.17mm for convex and non-convex shapes, respectively, while mean Dice values are 0.87±0.06 (convex) and 0.85±0.06 (non-convex). Three experimental cases are performed to validate the steering system. Mean targeting errors of 0.54±0.24, 1.50±0.82 and 1.82±0.40mm are obtained for steering in gelatin phantom, biological tissue and a human breast phantom, respectively. The achieved targeting errors suggest that our approach is sufficient for targeting lesions of 3mm radius that can be detected using clinical ultrasound imaging systems.","PeriodicalId":447761,"journal":{"name":"J. Medical Robotics Res.","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Medical Robotics Res.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/S2424905X16400055","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
Robot-assisted and ultrasound-guided needle insertion systems assist in achieving high targeting accuracy for different applications. In this paper, we introduce the use of Automated Breast Volume Scanner (ABVS) for scanning different soft tissue phantoms. The ABVS is a commercial ultrasound transducer used for clinical breast scanning. A preoperative scan is performed for three-dimensional (3D) target localization and shape reconstruction. The ultrasound transducer is also adapted to be used for tracking the needle tip during steering toward the localized targets. The system uses the tracked needle tip position as a feedback to the needle control algorithm. The bevel-tipped flexible needle is steered under ABVS guidance toward a target while avoiding an obstacle embedded in soft tissue phantom. We present experimental results for 3D reconstruction of different convex and non-convex objects with different sizes. Mean Absolute Distance (MAD) and Dice’s coefficient methods are used to evaluate the 3D shape reconstruction algorithm. The results show that the mean MAD values are 0.30±0.13mm and 0.34±0.17mm for convex and non-convex shapes, respectively, while mean Dice values are 0.87±0.06 (convex) and 0.85±0.06 (non-convex). Three experimental cases are performed to validate the steering system. Mean targeting errors of 0.54±0.24, 1.50±0.82 and 1.82±0.40mm are obtained for steering in gelatin phantom, biological tissue and a human breast phantom, respectively. The achieved targeting errors suggest that our approach is sufficient for targeting lesions of 3mm radius that can be detected using clinical ultrasound imaging systems.