Ultrasound (US) imaging is the most commonly performed cross-sectional diagnostic imaging modality in the practice of medicine. It is low-cost, non-ionizing, portable, and capable of real-time image acquisition and display. US is a rapidly evolving technology with significant challenges and opportunities. Challenges include high inter- and intra-operator variability and limited image quality control. Tremendous opportunities have arisen in the last decade as a result of exponential growth in available computational power coupled with progressive miniaturization of US devices. As US devices become smaller, enhanced computational capability can contribute significantly to decreasing variability through advanced image processing. In this paper, we review leading machine learning (ML) approaches and research directions in US, with an emphasis on recent ML advances. We also present our outlook on future opportunities for ML techniques to further improve clinical workflow and US-based disease diagnosis and characterization.

With the proliferation of portable sonography and the increase in nontraditional users, there is an increased need for automated decision support to standardize results. We developed algorithms to evaluate the presence or absence of "B-lines" on thoracic sonography as a marker for interstitial fluid. Algorithm performance was compared against an average of scores from 2 expert clinical sonographers. On the set for algorithm development, 90% of the scores matched the average expert scores with differences of 1 or less. On the independent set, a perfect match was achieved. We believe that these are the first reported results in computerized B-line scoring.

Intracardiac echocardiography (ICE) catheters enable high-quality ultrasound imaging within the heart, but their use in guiding procedures is limited due to the difficulty of manually pointing them at structures of interest. This paper presents the design and testing of a catheter steering model for robotic control of commercial ICE catheters. The four actuated degrees of freedom (4-DOF) are two catheter handle knobs to produce bi-directional bending in combination with rotation and translation of the handle. An extra degree of freedom in the system allows the imaging plane (dependent on orientation) to be directed at an object of interest. A closed form solution for forward and inverse kinematics enables control of the catheter tip position and the imaging plane orientation. The proposed algorithms were validated with a robotic test bed using electromagnetic sensor tracking of the catheter tip. The ability to automatically acquire imaging targets in the heart may improve the efficiency and effectiveness of intracardiac catheter interventions by allowing visualization of soft tissue structures that are not visible using standard fluoroscopic guidance. Although the system has been developed and tested for manipulating ICE catheters, the methods described here are applicable to any long thin tendon-driven tool (with single or bi-directional bending) requiring accurate tip position and orientation control.

A system for automatically pointing ultrasound (US) imaging catheters will enable clinicians to monitor anatomical structures and track instruments during interventional procedures. Off-the-shelf US catheters provide high quality US images from within the patient. While this method of imaging has been proven to be effective for guiding many interventional treatments, significant training is required to overcome the difficulty in manually steering the imager to point at desired structures. Our system uses closed-form four degree of freedom (DOF) kinematic solutions to automatically position the US catheter and point the imager. Algorithms for steering and imager pointing were developed for a range of useful diagnostic and interventional motions. The system was validated on a robotic test bed by steering the catheter within a water environment containing phantom objects. While the system described here was designed for pointing ultrasound catheters, these algorithms are applicable to accurate 4-DOF steering and orientation control of any long thin tendon-driven tool with single or bi-directional bending.