Pipette Hunter: Patch-Clamp Pipette Detection

Segmentation of objects with known geometries in an image is a wide research area. In this paper we show an energy minimization model to detect the tip of glass pipettes in microscopy images. The described model fits two rectangles with a common reference point to dark image regions, which are the sides of a pipette. The model is minimized using gradient descent. The low number of parameters result in a fast evolution and noise insensitivity. The algorithm is tested on label-free and fluorescent microscopy images. The error of the tip detection is only a few micrometers. Automatic pipette tip detection is a step forward to automate the patch-clamping process. The described method can be extended to 3 dimensions or other applications.