Enhancement of needle visualization and localization in ultrasound.

Purpose: This scoping review covers needle visualization and localization techniques in ultrasound, where localization-based approaches mostly aim to compute the needle shaft (and tip) location while potentially enhancing its visibility too.

Methods: A literature review is conducted on the state-of-the-art techniques, which could be divided into five categories: (1) signal and image processing-based techniques to augment the needle, (2) modifications to the needle and insertion to help with needle-transducer alignment and visibility, (3) changes to ultrasound image formation, (4) motion-based analysis and (5) machine learning.

Results: Advantages, limitations and challenges of representative examples in each of the categories are discussed.

CASPER: computer-aided segmentation of imperceptible motion-a learning-based tracking of an invisible needle in ultrasound.

Purpose: This paper presents a new micro-motion-based approach to track a needle in ultrasound images captured by a handheld transducer.

Methods: We propose a novel learning-based framework to track a handheld needle by detecting microscale variations of motion dynamics over time. The current state of the art on using motion analysis for needle detection uses absolute motion and hence work well only when the transducer is static.

Detection of an invisible needle in ultrasound using a probabilistic SVM and time-domain features.

We propose a novel learning-based approach to detect an imperceptible hand-held needle in ultrasound images using the natural tremor motion. The minute tremor induced on the needle however is also transferred to the tissue in contact with the needle, making the accurate needle detection a challenging task. The proposed learning-based framework is based on temporal analysis of the phase variations of pixels to classify them according to the motion characteristics.

Three-Dimensional Ultrasound-Guided Real-Time Midline Epidural Needle Placement with Epiguide: A Prospective Feasibility Study.

Current 2-D ultrasound technology is unable to perform a midline neuraxial needle insertion under real-time ultrasound guidance using a standard needle and without an assistant. The aim of the work described here was to determine the feasibility of a new technology providing such capability, starting with a study evaluating the selected puncture site. A novel 3-D ultrasound imaging technique was designed using thick-slice rendering in conjunction with a custom needle guide (3DUS + Epiguide).

Spectral analysis of the tremor motion for needle detection in curvilinear ultrasound via spatiotemporal linear sampling.

Purpose: This paper presents a new approach to detect a standard handheld needle in ultrasound-guided interventions.

Methods: Our proposal is to use natural hand tremor, which causes minute displacement of the needle, to detect the needle in ultrasound B-mode images. Subtle displacements arising from tremor motion have a periodic pattern which is usually imperceptible to the naked eye in the B-mode image.

Needle Trajectory and Tip Localization in Real-Time 3-D Ultrasound Using a Moving Stylus.

Described here is a novel approach to needle localization in 3-D ultrasound based on automatic detection of small changes in appearance on movement of the needle stylus. By stylus oscillation, including its full insertion into the cannula to the tip, the image processing techniques can localize the needle trajectory and the tip in the 3-D ultrasound volume. The 3-D needle localization task is reduced to two 2-D localizations using orthogonal projections.

Sex and Smoking Status Effects on the Early Detection of Early Lung Cancer in High-Risk Smokers Using an Electronic Nose.

Objective: Volatile organic compounds (VOCs) in exhaled breath as measured by electronic nose (e-nose) have utility as biomarkers to detect subjects at risk of having lung cancer in a screening setting. We hypothesize that breath analysis using an e-nose chemo-resistive sensor array could be used as a screening tool to discriminate patients diagnosed with lung cancer from high-risk smokers.

Methods: Breath samples from 191 subjects-25 lung cancer patients and 166 high-risk smoker control subjects without cancer-were analyzed.