Characterizing and identifying biological structure

Abstract

Embodiments described relate to techniques for identifying and characterizing biological structures using machine learning techniques. These techniques may be employed to enable a device to identify the particular type of tissue and/or cells (e.g., platelets, smooth muscle cells, or endothelial cells) in, for example, a biological structure, which may be a tissue or a lesion of a duct (e.g., vasculature) in an animal (e.g., a human or non-human animal), among other structures. The machine learning techniques may use raw impedance spectroscopy measurement data in addition to values derived from that raw data. In addition, the machine learning techniques may be used to select frequencies at which to measure impedance and select features to extract from the measured impedance at the selected frequencies to arrive at a small set of frequencies that allow for reliable differentiation.