A new scheme for curved needle segmentation in three-dimensional ultrasound images

Authors:
Mohammad Aboofazeli;Purang Abolmaesumi;Parvin Mousavi;Gabor Fichtinger
Affiliations:
School of Computing, Queen’s University, Kingston, ON, Canada;School of Computing, Queen’s University, Kingston, ON, Canada;School of Computing, Queen’s University, Kingston, ON, Canada;School of Computing, Queen’s University, Kingston, ON, Canada
Venue:
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Year:
2009

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Abstract

Ultrasound image guided needle insertion is the method of choice for a wide variety of medical diagnostic and therapeutic procedures. When flexible needles are inserted in soft tissue, these needles generally follow a curved path. Segmenting the trajectory of the needles in ultrasound images will facilitate guiding them within the tissue. In this paper, a novel algorithm for curved needle segmentation in three-dimensional (3D) ultrasound images is presented. The algorithm is based on the projection of a filtered 3D image onto a two-dimensional (2D) image. Detection of the needle in the resulting 2D image determines a surface on which the needle is located. The needle is then segmented on the surface. The proposed technique is able to detect needles without any previous assumption about the needle shape, or any a priori knowledge about the needle insertion axis line.