Perception of operator influences ultrasound image acquisition and processing. Lower costs are attracting new users to medical ultrasound. Anticipating an increase in this trend, we conducted a study to quantify the variability in ultrasonic measurements made by novice users and identify methods to reduce it. We designed a protocol with four presets and trained four new users to scan and manually measure the head circumference of a fetal phantom with an ultrasound scanner. In the first phase, the users followed this protocol in seven distinct sessions. They then received feedback on the quality of the scans from an expert. In the second phase, two of the users repeated the entire protocol aided by visual cues provided to them during scanning. We performed off-line measurements on all the images using a fully automated algorithm capable of measuring the head circumference from fetal phantom images. The ground truth (198.1±1.6 mm) was based on sixteen scans and measurements made by an expert. Our analysis shows that: (1) the inter-observer variability of manual measurements was 5.5 mm, whereas the inter-observer variability of automated measurements was only 0.6 mm in the first phase (2) consistency of image appearance improved and mean manual measurements was 4-5 mm closer to the ground truth in the second phase (3) automated measurements were more precise, accurate and less sensitive to different presets compared to manual measurements in both phases. Our results show that visual aids and automation can bring more reproducibility to ultrasonic measurements made by new users.
Acquisition of a clinically acceptable scan plane is a pre-requisite for ultrasonic measurement of anatomical
features from B-mode images. In obstetric ultrasound, measurement of gestational age predictors, such as
biparietal diameter and head circumference, is performed at the level of the thalami and cavum septum pelucidi.
In an accurate scan plane, the head can be modeled as an ellipse, the thalami looks like a butterfly, the cavum
appears like an empty box and the falx is a straight line along the major axis of a symmetric ellipse inclined either
parallel to or at small angles to the probe surface. Arriving at the correct probe placement on the mother's belly
to obtain an accurate scan plane is a task of considerable challenge especially for a new user of ultrasound. In
this work, we present a novel automated learning-based algorithm to identify an acceptable fetal head scan plane.
We divide the problem into cranium detection and a template matching to capture the composite "butterfly"
structure present inside the head, which mimics the visual cues used by an expert. The algorithm uses the stateof-
the-art Active Appearance Models techniques from the image processing and computer vision literature and
tie them to presence or absence of the inclusions within the head to automatically compute a score to represent
the goodness of a scan plane. This automated technique can be potentially used to train and aid new users of
Fetal bi-parietal diameter (BPD) is known to provide a reliable estimate of gestational age (GA) of a fetus in the first half
of pregnancy. In this paper, we present an automated method to identify and measure BPD from B-mode ultrasound
images of fetal head. The method (a) automatically detects and places a region-of-interest on the head based on a prior
work in our group (b) utilizes the concept of phase congruency for edge detection and (c) employs a cost function to
identify the third ventricle inside the head (d) measures the BPD along the perpendicular bisector of occipital frontal
diameter (OFD) from the outer rim of the cranium closer to the transducer to the inner rim of the cranium away from the
transducer. The cost function is premised on the distribution of anatomical shape, size and presentation of the third
ventricle in images that adhere to clinical guidelines describing the scan plane for BPD measurement. The OFD is
assumed to lie along the third ventricle. The algorithm has been tested on 137 images acquired from four different
scanners. Based on GA estimates and their bounds specified in Standard Obstetric Tables, the GA predictions from
automated measurements are found to be within ±2SD of GA estimates from manual measurements by the operator and a
second expert radiologist in 98% of the cases. The method described in this paper can also be adapted to assess the
accuracy of the scan plane based on the presence/absence of the third ventricle.
Femur bone length is used in the assessment of fetal development and in the prediction of gestational age (GA). In this
paper, we present a completely automated two-step method for identifying fetal femur and measuring its length from 2D
ultrasound images. The detection algorithm uses a normalized score premised on the distribution of anatomical shape,
size and presentation of the femur bone in clinically acceptable scans. The measurement process utilizes a polynomial
curve fitting technique to determine the end-points of the bone from a 1D profile that is most distal from the transducer
surface. The method has been tested with manual measurements made on 90 third trimester femur images by two radiologists. The measurements made by the experts are strongly correlated (Pearson's coefficient = 0.95). Likewise, the algorithm estimate is strongly correlated with expert measurements (Pearson's coefficient = 0.92 and 0.94). Based on GA estimates and their bounds specified in Standard Obstetric Tables, the GA predictions from automated measurements are found to be within ±2SD of GA estimates from both manual measurements in 89/90 cases and within ±3SD in all 90 cases. The method presented in this paper can be adapted to perform automatic measurement of other fetal limbs.
We present a method for design and use of a digital mouse phantom for small animal optical imaging. We map the boundary of a mouse model from magnetic resonance imaging (MRI) data through image processing algorithms and discretize the geometry by a finite element (FE) descriptor. We use a validated FE implementation of the three-dimensional (3-D) diffusion equation to model transport of near infrared (NIR) light in the phantom with a mesh resolution optimized for representative tissue optical properties on a computing system with 8-GB RAM. Our simulations demonstrate that a section of the mouse near the light source is adequate for optical system design and that the variation of intensity of light on the boundary is well within typical noise levels for up to 20% variation in optical properties and nodes used to model the boundary of the phantom. We illustrate the use of the phantom in setting goals for specific binding of targeted exogenous fluorescent contrasts based on anatomical location by simulating a nearly tenfold change in the detectability of a 2-mm-deep target depending on its placement. The methodology described is sufficiently general and may be extended to generate digital phantoms for designing clinical optical imaging systems.
As the imaging modalities used in medicine transition to increasingly three-dimensional data the question of
how best to interact with and analyze this data becomes ever more pressing. Immersive virtual reality
systems seem to hold promise in tackling this, but how individuals learn and interact in these environments is
not fully understood. Here we will attempt to show some methods in which user interaction in a virtual reality
environment can be visualized and how this can allow us to gain greater insight into the process of
interaction/learning in these systems. Also explored is the possibility of using this method to improve
understanding and management of ergonomic issues within an interface.
Accurate calculation of internal fluence excited in tissue from an optical source can be used for predicting the performance of fluorescent contrast agents for clinical applications. Solutions of excitation fluence for a steady-state Monte Carlo model and a finite element implementation of the 3d diffusion equation have been compared up to depths of 20mm from a point source located on top of a homogeneous cylindrical phantom for a range of reduced scattering-to-absorption ratios. Differences between the fluence calculated by Monte Carlo and diffusion model is found to be dependent on the transport mean free path (mfp), size of the phantom in relation to the penetration depth, distance from the source and mesh resolution. The differences are small at depths ~ mfp and peak at depths ~2mfp. The differences should ideally reduce to zero at large depths but the magnitude of the differences tend to increase due to the finite boundary in the diffusion model. As an example, for a mfp = 0.817mm similar in magnitude to mesh resolution, diffusion fluence at 1mm, 2mm, 10mm and 14mm is 76%, 59%, 66% and 63% respectively of Monte Carlo fluence. For large mfp's characteristic of non- diffusive regimes, diffusion model overestimates fluence at distances less than one mfp. This work demonstrates that mean free path and mesh resolution are the critical parameters that distinguish the performance of Monte Carlo and diffusion models to define error margins that could be utilized for predictive assessment of imageability of fluorescent agents using the diffusion model.
A diffusion approximation to the radiative transfer in a medium with varying refractive index has been proposed as a theoretical model for the ultrasonic tagging of fluorescence or FluoroSound, in a scattering medium. It has been found that the diffuse modulation is a defocusing effect. Defocusing is related to scatter - more the scatter, more the defocusing and there exists a component of the defocusing effect of scatter at the ultrasonic frequency. This is in contrast to the modulation for ballistic photons that originates in the focusing effect of the acoustic lens created by the ultrasonic wave. Simulations with circular phantoms of 1.5 and 2.0cm radius have shown that defocusing is minimum when the acoustic lens is midway between the source and the detector. These results are consistent with physics and demonstrate the capability of the model to function as a predictive tool for FluoroSound instrument design. Both ballistic and diffuse FluoroSound signatures can help in the simultaneous localization of the anomaly and determination of its optical properties. As an adjunct, optimally designed ultrasound beams can be also used to enhance diffuse photon modulation signal through acoustic guidance. Optical properties provide a way to discriminate between normal and diseased tissue. FluoroSound could therefore potentially achieve a fusion of anatomical and functional information non-invasively in a single measurement. The additional information made available by this method will improve the speed and accuracy of optical imaging as a tool in the identification and validation of targets.