Entropy vs. Energy Waveform Processing: A Comparison Based on the Heat Equation

Ultrasound Imaging with Flexible Array Transducer for Pancreatic Cancer Radiation Therapy

Pancreatic cancer with less than 10% 3-year survival rate is one of deadliest cancer types and greatly benefits from enhanced radiotherapy. Organ motion monitoring helps spare the normal tissue from high radiation and, in turn, enables the dose escalation to the target that has been shown to improve the effectiveness of RT by doubling and tripling post-RT survival rate. The flexible array transducer is a novel and promising solution to address the limitation of conventional US probes. We proposed a novel shape estimation for flexible array transducer using two sequential algorithms: (i) an optical tracking-based system that uses the optical markers coordinates attached to the probe at specific positions to estimate the array shape in real-time and (ii) a fully automatic shape optimization algorithm that automatically searches for the optimal array shape that results in the highest quality reconstructed image. We conducted phantom and in vivo experiments to evaluate the estimated array shapes and the accuracy of reconstructed US images. The proposed method reconstructed US images with low full-width-at-half-maximum (FWHM) of the point scatters, correct aspect ratio of the cyst, and high-matching score with the ground truth. Our results demonstrated that the proposed methods reconstruct high-quality ultrasound images with significantly less defocusing and distortion compared with those without any correction. Specifically, the automatic optimization method reduced the array shape estimation error to less than half-wavelength of transmitted wave, resulting in a high-quality reconstructed image.

Application of entropy and signal energy for ultrasound-based classification of three-dimensional printed polyetherketoneketone components

This paper describes a preliminary method for the classification of annealed and unannealed polyetherketoneketone (PEKK) components manufactured using a material extrusion three-dimensional (3D) printing process. PEKK is representative of a class of high-performance thermoplastics that are increasingly employed as feedstocks for use in 3D printing. PEKK components may be used continuously at elevated temperatures, are chemically resistant, and able to withstand large mechanical loads. These properties render PEKK suitable as a metal component replacement in aerospace applications, high-temperature industrial applications, and surgical implants. The structure of PEKK is semi-crystalline with the specific crystallinity correlating to the final properties during application, making determination of this property crucial. This study compares three different signal processing techniques intended to distinguish annealed (high crystallinity) from unannealed (low crystallinity) components using backscattered ultrasound. The first is energy-based and is unable to detect annealing. The second two are based on different entropies of the backscattered signal: a limiting form of Renyi's entropy and a limiting form of joint entropy. The joint entropy values for the annealed and unannealed specimens fall into two non-overlapping intervals and have a statistical separation of two standard deviations.

Resolution of Murine Toxic Hepatic Injury Quantified With Ultrasound Entropy Metrics

Image-based classification of liver disease generally lacks specificity for distinguishing between acute, resolvable injury and chronic irreversible injury. We propose that ultrasound radiofrequency data acquired in vivo from livers subjected to toxic drug injury can be analyzed with information theoretic detectors to derive entropy metrics, which classify a statistical distribution of pathologic scatterers that dissipate over time as livers heal. Here we exposed 38 C57BL/6 mice to carbon tetrachloride to cause liver damage, and imaged livers in vivo 1, 4, 8, 12 and 18 d after exposure with a broadband 15-MHz probe. Selected entropy metrics manifested monotonic recovery to normal values over time as livers healed, and were correlated directly with progressive restoration of liver architecture by histologic assessment (r² ≥ 0.95, p < 0.004). Thus, recovery of normal liver microarchitecture after toxic exposure can be delineated sensitively with entropy metrics.

Acoustic firearm discharge detection and classification in an enclosed environment

Two different signal processing algorithms are described for detection and classification of acoustic signals generated by firearm discharges in small enclosed spaces. The first is based on the logarithm of the signal energy. The second is a joint entropy. The current study indicates that a system using both signal energy and joint entropy would be able to both detect weapon discharges and classify weapon type, in small spaces, with high statistical certainty.