Browsing by Subject "Resolution"

The purpose of this dissertation was to develop methods of measuring patient-specific image quality in computed tomography. The methods developed in this dissertation enable noise power spectrum, low contrast resolution, and ultimately a detectability index to be measured in a patient-specific manner. The project is divided into three part: 1) demonstrating the utility of currently developed patient-specific measures of image quality, 2) developing a method to estimate noise power spectrum and low contrast task transfer function from patient images, 3) and applying the extended metrology to the calculation of a patient-specific and task-specific detectability index of the future.In part 1, (chapters 2 and 3) the value of patient-specific image quality is demonstrated in two ways. First, patient-specific measures of noise magnitude and high-contrast resolution were deployed on a broad clinical dataset of chest and abdomen-pelvis exams. Image quality and dose were measured for 87,629 cases across 97 medical facilities, and variability in each outcome are reported. Such measurements of variability would be impossible in a phantom-derived image quality paradigm. Secondly, patient-specific measures of noise magnitude and high-contrast resolution were combined with a phantom-derived noise power spectrum to yield a detectability index. The hybrid (patient, and phantom-derived) detectability index was measured and retrospectively compared to the results of a detection observer study. The results show that the measured hybrid detectability index is shown to be correlated with human observer detection performance, further demonstrating the value of measuring patient-specific image quality. In part 2, (chapters 4 and 5) two image quality aspects are extended from a phantom-derived to a patient-specific paradigm. In chapter 4, a method to measure noise power spectrum from patient images is developed and validated using virtual imaging trial and physical phantom data. The method is applied to unseen clinical cases to demonstrate its feasibility, and the method’s sensitivity to expected trends across image reconstructions. Since the method relies on a sufficient area within the patient’s liver to make a measurement, the sensitivity of measurement accuracy of the method region size is assessed. Results show that the measurements can be accurate with as few as 106 included pixels, and that measurements are sensitive to ground truth differences in reconstruction algorithm. In chapter 5, a method to measure low contrast resolution from patient images is developed and validated using low contrast insert phantom scans. The method uses a support vector machine to learn the connection between the patient-specific noise power spectrum measured in chapter 4 and the low contrast task transfer function. The estimation method is compared to clinical alternative and results show that it is more accurate on the basis of RMSE for iterative reconstructions (especially high strength reconstructions). In part 3, (chapter 6 and appendix section 8.1) the developed patient-specific image quality metrology are applied to calculated fully patient-specific detectability index. Here, patient-specific image quality measures are re-applied to the detectability index calculations from chapter 3, converting the calculations from a hybrid method to a fully patient-specific method. To do so, the patient-specific noise power spectrum estimates from chapter 4 were combined with the patient-specific low contrast task transfer functions from chapter 5 to inform the detectability index calculations. The purpose of this chapter was to show the positive impact of measuring a task-based measure of image quality in a fully patient-specific paradigm. The results show that the fully patient-specific detectability index show a statistically significant improvement in its relation with human detection accuracy over the hybrid measurements. This section also served as an indirect validation methodologies in chapters 4 and 5. Finally, all patient-specific measures are deployed over a variety of clinical cases to demonstrate feasibility of using the methods to monitor image quality. In conclusion, this dissertation developed methods to assess task based and task generic image quality directly from patient images, and demonstrated the utility and value of patient-specific image quality assessment.

Clutter is a problematic noise artifact in a variety of ultrasound applications. Clinical tasks complicated by the presence of clutter include detecting cancerous lesions in abdominal organs (e.g. livers, bladders) and visualizing endocardial borders to assess cardiovascular health. In this dissertation, an analytical expression for contrast loss due to clutter is derived, clutter is quantified in abdominal images, and sources of abdominal clutter are identified. Novel clutter reduction methods are also presented and tested in abdominal and cardiac images.

One of the novel clutter reduction methods is Short-Lag Spatial Coherence (SLSC) imaging. Instead of applying a conventional delay-and-sum beamformer to measure the amplitude of received echoes and form B-mode images, the spatial coherence of received echoes are measured to form SLSC images. The world's first SLSC images of simulated, phantom, and in vivo data are presented herein. They demonstrate reduced clutter and improved contrast, contrast-to-noise, and signal-to-noise ratios compared to conventional B-mode images. In addition, the resolution characteristics of SLSC images are quantified and compared to resolution in B-mode images.

A clinical study with 14 volunteers was conducted to demonstrate that SLSC imaging offers 19-33% improvement in the visualization of endocardial borders when the quality of B-mode images formed from the same echo data was poor. There were no statistically significant improvements in endocardial border visualization with SLSC imaging when the quality of matched B-mode images was medium to good.

Proposed is a method for investigating optimal acquisition parameters in NSECT, neutron stimulated emission computed tomography, for good image quality and low dose for diagnosing liver and breast cancers. These parameters include the number of angles, number of translations per angle, beam width, and beam width spacing. These parameters will affect dose, which will increase with increasing total neutron flux. Therefore, a balance must be achieved for the parameters mentioned above, to yield a desired dose limit and tolerable spatial resolution necessary for liver and breast cancer diagnosis.

Using Monte Carlo simulation toolkit GEANT4, the effects of beam spread due to neutron elastic scatter was explored. Then, a geometrical water torso phantom with slanted edge solid iron phantom was run for different acquisition parameters, and an MTF was taken to determine resolution for each set. For dose considerations, two anthropomorphic voxelized phantoms, one with liver cancer lesions, and one with breast cancer lesions, were scanned with the same parameter sets, and organ doses and DVHs, dose volume histograms, was computed for each set. In addition, images of the phantom in the lesion plane were reconstructed for those parameter sets showing best resolution and lowest dose.

It is found that beam spread due to elastic scatter off of Hydrogen atoms is negligible for all beam widths. For optimal resolution in the primary breast phantom, it was found that acquisition parameters of a 5 mm beam, with no gaps, with any of the five angles provided the superior resolution. For the optimal resolution in the liver, it was found that down sampling angles and introducing gaps between projections greatly affected image accuracy and resolution. Also, the 5 mm beam width provided better geometrical accuracy, but the 1 cm bream width provided slightly better resolution.

Organ doses are computed for the primary organ and organs at risk for each parameter set at 500 K neutrons per projection. For a scan of the full volume of the liver, liver organ doses ranged from 25.83 to 0.19 mSv. For the same scan, the organ doses for the heart ranged from 0.18 to 0.05 mSv. For a scan with the same pool of acquisition parameters of the full volume of the breast, breast organ doses ranged from 49.87 to 0.38 mSv. Furthermore, the DVHs for both scans showed a very steep drop-off at low dose bins for secondary organs at risk and a reasonable drop-off for the primary organ.

In choosing the optimal acquisition parameters using both resolution and dose, a metric equal to resolution times dose is used, in which low values are optimal. An upper threshold for the metric was chosen based on dose values in currently used medical imaging modalities. A pool of optimal parameter sets was then identified using the metric. To further identify the optimum, a metric estimating geometrical accuracy of the reconstructed square was used. For the breast scan, the optimal parameter set was a 1 cm beam width, with 0 mm a gap, with 12 angles. For the liver scan, the optimal parameter set was a 1 cm beam width, with a 0 mm gap, with 36 angles.

Finally, reconstructed images of the anthropomorphic scans using the super sampled geometry in the liver scan showed one lesion, using images of iron and phosphorous. With more degraded image quality, reconstructed images of the breasts using the super sampled geometry showed only the three cm lesion accurately. The images reconstructed from the optimal set identified for liver scans also showed the larger lesion, except with some noise from the presence of iron and phosphorous in other organs. The images reconstructed from the optimal set identified for the breast scans had a similar result to that of the super-sampled case, albeit with lower contrast. The least sampled case for both scans were found to be diagnostically useless. From these anthropomorphic images, this work demonstrates that in-vivo imaging of breast and liver cancers may be potentially possible with NSECT at a low dose.

Sea urchins and brittle stars lack eyes, yet nonetheless are capable of vision, or the detection and resolution of spatial images and detail. Their vision, according to what is known today, is mediated through a light-sensing system that extends across the body and is processed via a decentralized nervous system. This is different from two-eyed and even most multi-eyed animals, where light is collected via discrete organs (eyes or eye cups) and processed in a brain or central ganglion. As benthic marine invertebrates, vision may be useful to sea urchins and brittle stars for navigating, finding shelter, or identifying predators. Although photoreceptor cells have been identified in brittle stars, much remains unknown about vision and light responses in both groups and the echinoderms as a whole (sea urchins, brittle stars, sea stars, sea cucumbers, and feather stars). My dissertation examines some of the gaps in this field of inquiry. I investigate (1) the potential ecological correlates of a sea urchin trait thought to mediate spatial vision, (2) how various regions of the urchin body differ in their sensitivity to light, and (3) if brittle stars are capable learning to associate a darkness cue with the presentation of food.

First, I performed a comparative study on the density of spines on sea urchins. As stated previously, sea urchins do not have eyes yet they are capable of resolving coarse images. One suggestion as to the mechanism of this capability is that the spines shade off-axis light from reaching the photosensitive test (skeleton). Following this hypothesis, the density of spines across the body determines the resolution (or sharpness) of vision by restricting the incidence of light on the photosensitive skin of the animal, creating receptive areas of different minimum resolvable angles. Previous studies have shown that predicted resolutions in several species closely match behaviorally-determined resolutions, ranging from 10° to 33°. Here we present a comparative morphological survey of spine density with species representatives from 22 of the 24 families of regular sea urchins (Class Echinoidea) in order to better understand the relative influences of phylogenetic history and three visually-relevant environmental variables on this trait. We estimated predicted resolutions by calculating spine densities from photographs of spineless sea urchin tests (skeletons). Analyses showed a strong phylogenetic signal in spine density differences between species. Phylogenetically-corrected Generalized Least Squares (PGLS) models incorporating all habitat parameters were the most supported, and no particular parameter was significantly correlated with spine density. Spine density is subject to multiple, overlapping selective pressures and therefore it is possible that either: 1) spine density does not mediate spatial vision in echinoids, or 2) visual resolution via spine density is a downstream consequence of sea urchin morphology rather than a driving force of adaptation in these animals.

Second, I examined the sensitivity to light on different parts of the body of the urchin species Lytechinus variegatus. The sensitivity of an eye is important to understand because it not only determines the light levels under which an eye can function but also indirectly affects how sharp the vision can be. It is unknown how sensitivity maps across the body in urchins, which may have implications for how various parts of the body are used in visual tasks. I tested the behavioral sensitivity response of L. variegatus to light on different regions of the body, using positive or negative phototaxis as response criteria. I tested the ambulacral region first, because this has been shown to be more sensitive to light than the interambulacral region in other urchin species. Individuals of L. variegatus were negatively phototactic to the brightest light (10,000 lux) and exhibited positive phototaxis to any dimmer light, responding to as little as 10 lux (or about the amount of ambient light in late civil twilight). Next, I tested the relative sensitivity response of the ambulacrum and interambulacrum, the two regions of the body, and confirmed that the ambulacrum is the more sensitive of the two in L. variegatus. Finally, I tested the relative sensitivity response of different angular heights (elevations) on the urchin body, along the oral-aboral axis, as these may be ecologically meaningful to the animal. There was a behavioral shift as elevation increased. Bright (10,000 lux) light at 0° (the equator of the animal) caused positive phototaxis; at 30° above the equator, roughly an equal number of urchins moved towards and away from the light; and at 60° above the equator the light caused a negative phototaxis response. The negative phototaxis observed with the light at a 60° elevation on the animal may have ecological consequences or indicate that this region is less sensitive to light. The data from this study can inform which regions and structures future studies may want to target for sensitivity and vision studies in L. variegatus.

Third, I tested whether individuals of the brittle star species Ophiocoma echinata were able to associate a period of darkness with the presentation of a food reward. Like other members of Phylum Echinodermata, the ophiuroid nervous system is decentralized, consisting of five radially arranged ganglia joined by a central nerve ring. While operant and classical conditioning have been observed in asteroids in a limited number of studies, members of the other echinoderm classes remain relatively untested. A group of individually housed Ophiocoma in an experimental group were trained by only presenting food during a period of darkness, while control group animals were fed under regular daytime room lights many hours after a period of darkness of the same duration. After the training period, the experimental group demonstrated they had learned to associate the two cues by regularly emerging during the dark period even when no food was presented. The untrained control animals, as well as pre-training experimental animals, did not emerge during the dark periods, as no food was presented. There was, however, significant variation within the experimental group in terms of the number of times individuals displayed the learned behavior and how quickly animals learned the association. This study shows that classical conditioning is possible in a class of animals without centralized nervous systems.

These results contribute to greater understandings of resolution, sensitivity, and light-guided tasks in the echinoderms which have implications for the visual ecology of these species as well as the study of sensing and processing in decentralized systems.