Spatio-temporal deep learning models for tip force estimation during needle insertion.

ABSTRACT:

Purpose

Precise placement of needles is a challenge in a number of clinical applications such as brachytherapy or biopsy. Forces acting at the needle cause tissue deformation and needle deflection which in turn may lead to misplacement or injury. Hence, a number of approaches to estimate the forces at the needle have been proposed. Yet, integrating sensors into the needle tip is challenging and a careful calibration is required to obtain good force estimates.

Methods

We describe a fiber-optic needle tip force sensor design using a single OCT fiber for measurement. The fiber images the deformation of an epoxy layer placed below the needle tip which results in a stream of 1D depth profiles. We study different deep learning approaches to facilitate calibration between this spat

SUBMITTER: Gessert N 

PROVIDER: S-EPMC6785597 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature