Matching Items (501)
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Description
Surgery as a profession requires significant training to improve both clinical decision making and psychomotor proficiency. In the medical knowledge domain, tools have been developed, validated, and accepted for evaluation of surgeons' competencies. However, assessment of the psychomotor skills still relies on the Halstedian model of apprenticeship, wherein surgeons are

Surgery as a profession requires significant training to improve both clinical decision making and psychomotor proficiency. In the medical knowledge domain, tools have been developed, validated, and accepted for evaluation of surgeons' competencies. However, assessment of the psychomotor skills still relies on the Halstedian model of apprenticeship, wherein surgeons are observed during residency for judgment of their skills. Although the value of this method of skills assessment cannot be ignored, novel methodologies of objective skills assessment need to be designed, developed, and evaluated that augment the traditional approach. Several sensor-based systems have been developed to measure a user's skill quantitatively, but use of sensors could interfere with skill execution and thus limit the potential for evaluating real-life surgery. However, having a method to judge skills automatically in real-life conditions should be the ultimate goal, since only with such features that a system would be widely adopted. This research proposes a novel video-based approach for observing surgeons' hand and surgical tool movements in minimally invasive surgical training exercises as well as during laparoscopic surgery. Because our system does not require surgeons to wear special sensors, it has the distinct advantage over alternatives of offering skills assessment in both learning and real-life environments. The system automatically detects major skill-measuring features from surgical task videos using a computing system composed of a series of computer vision algorithms and provides on-screen real-time performance feedback for more efficient skill learning. Finally, the machine-learning approach is used to develop an observer-independent composite scoring model through objective and quantitative measurement of surgical skills. To increase effectiveness and usability of the developed system, it is integrated with a cloud-based tool, which automatically assesses surgical videos upload to the cloud.
ContributorsIslam, Gazi (Author) / Li, Baoxin (Thesis advisor) / Liang, Jianming (Thesis advisor) / Dinu, Valentin (Committee member) / Greenes, Robert (Committee member) / Smith, Marshall (Committee member) / Kahol, Kanav (Committee member) / Patel, Vimla L. (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The apolipoprotein E (APOE) e4 genotype is the most prevalent known genetic risk factor for Alzheimer's disease (AD). In this paper, we examined the longitudinal effect of APOE e4 on hippocampal morphometry in Alzheimer's Disease Neuroimaging Initiative (ADNI). Generally, atrophy of hippocampus has more chance occurs in AD patients who

The apolipoprotein E (APOE) e4 genotype is the most prevalent known genetic risk factor for Alzheimer's disease (AD). In this paper, we examined the longitudinal effect of APOE e4 on hippocampal morphometry in Alzheimer's Disease Neuroimaging Initiative (ADNI). Generally, atrophy of hippocampus has more chance occurs in AD patients who carrying the APOE e4 allele than those who are APOE e4 noncarriers. Also, brain structure and function depend on APOE genotype not just for Alzheimer's disease patients but also in health elderly individuals, so APOE genotyping is considered critical in clinical trials of Alzheimer's disease. We used a large sample of elderly participants, with the help of a new automated surface registration system based on surface conformal parameterization with holomorphic 1-forms and surface fluid registration. In this system, we automatically segmented and constructed hippocampal surfaces from MR images at many different time points, such as 6 months, 1- and 2-year follow up. Between the two different hippocampal surfaces, we did the high-order correspondences, using a novel inverse consistent surface fluid registration method. At each time point, using Hotelling's T^2 test, we found significant morphological deformation in APOE e4 carriers relative to noncarriers in the entire cohort as well as in the non-demented (pooled MCI and control) subjects, affecting the left hippocampus more than the right, and this effect was more pronounced in e4 homozygotes than heterozygotes.
ContributorsLi, Bolun (Author) / Wang, Yalin (Thesis advisor) / Maciejewski, Ross (Committee member) / Liang, Jianming (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Detecting anatomical structures, such as the carina, the pulmonary trunk and the aortic arch, is an important step in designing a CAD system of detection Pulmonary Embolism. The presented CAD system gets rid of the high-level prior defined knowledge to become a system which can easily extend to detect other

Detecting anatomical structures, such as the carina, the pulmonary trunk and the aortic arch, is an important step in designing a CAD system of detection Pulmonary Embolism. The presented CAD system gets rid of the high-level prior defined knowledge to become a system which can easily extend to detect other anatomic structures. The system is based on a machine learning algorithm --- AdaBoost and a general feature --- Haar. This study emphasizes on off-line and on-line AdaBoost learning. And in on-line AdaBoost, the thesis further deals with extremely imbalanced condition. The thesis first reviews several knowledge-based detection methods, which are relied on human being's understanding of the relationship between anatomic structures. Then the thesis introduces a classic off-line AdaBoost learning. The thesis applies different cascading scheme, namely multi-exit cascading scheme. The comparison between the two methods will be provided and discussed. Both of the off-line AdaBoost methods have problems in memory usage and time consuming. Off-line AdaBoost methods need to store all the training samples and the dataset need to be set before training. The dataset cannot be enlarged dynamically. Different training dataset requires retraining the whole process. The retraining is very time consuming and even not realistic. To deal with the shortcomings of off-line learning, the study exploited on-line AdaBoost learning approach. The thesis proposed a novel pool based on-line method with Kalman filters and histogram to better represent the distribution of the samples' weight. Analysis of the performance, the stability and the computational complexity will be provided in the thesis. Furthermore, the original on-line AdaBoost performs badly in imbalanced conditions, which occur frequently in medical image processing. In image dataset, positive samples are limited and negative samples are countless. A novel Self-Adaptive Asymmetric On-line Boosting method is presented. The method utilized a new asymmetric loss criterion with self-adaptability according to the ratio of exposed positive and negative samples and it has an advanced rule to update sample's importance weight taking account of both classification result and sample's label. Compared to traditional on-line AdaBoost Learning method, the new method can achieve far more accuracy in imbalanced conditions.
ContributorsWu, Hong (Author) / Liang, Jianming (Thesis advisor) / Farin, Gerald (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2011
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Description
Unsupervised learning of time series data, also known as temporal clustering, is a challenging problem in machine learning. This thesis presents a novel algorithm, Deep Temporal Clustering (DTC), to naturally integrate dimensionality reduction and temporal clustering into a single end-to-end learning framework, fully unsupervised. The algorithm utilizes an autoencoder for

Unsupervised learning of time series data, also known as temporal clustering, is a challenging problem in machine learning. This thesis presents a novel algorithm, Deep Temporal Clustering (DTC), to naturally integrate dimensionality reduction and temporal clustering into a single end-to-end learning framework, fully unsupervised. The algorithm utilizes an autoencoder for temporal dimensionality reduction and a novel temporal clustering layer for cluster assignment. Then it jointly optimizes the clustering objective and the dimensionality reduction objective. Based on requirement and application, the temporal clustering layer can be customized with any temporal similarity metric. Several similarity metrics and state-of-the-art algorithms are considered and compared. To gain insight into temporal features that the network has learned for its clustering, a visualization method is applied that generates a region of interest heatmap for the time series. The viability of the algorithm is demonstrated using time series data from diverse domains, ranging from earthquakes to spacecraft sensor data. In each case, the proposed algorithm outperforms traditional methods. The superior performance is attributed to the fully integrated temporal dimensionality reduction and clustering criterion.
ContributorsMadiraju, NaveenSai (Author) / Liang, Jianming (Thesis advisor) / Wang, Yalin (Thesis advisor) / He, Jingrui (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Breast microcalcifications are a potential indicator of cancerous tumors. Current visualization methods are either uncomfortable or impractical. Impedance measurement studies have been performed, but not in a clinical setting due to a low sensitivity and specificity. We are hoping to overcome this challenge with the development of a highly accurate

Breast microcalcifications are a potential indicator of cancerous tumors. Current visualization methods are either uncomfortable or impractical. Impedance measurement studies have been performed, but not in a clinical setting due to a low sensitivity and specificity. We are hoping to overcome this challenge with the development of a highly accurate impedance probe on a biopsy needle. With this technique, microcalcifications and the surrounding tissue could be differentiated in an efficient and comfortable manner than current techniques for biopsy procedures. We have developed and tested a functioning prototype for a biopsy needle using bioimpedance sensors to detect microcalcifications in the human body. In the final prototype a waveform generator sends a sin wave at a relatively low frequency(<1KHz) into the pre-amplifier, which both stabilizes and amplifies the signal. A modified howland bridge is then used to achieve a steady AC current through the electrodes. The voltage difference across the electrodes is then used to calculate the impedance being experienced between the electrodes. In our testing, the microcalcifications we are looking for have a noticeably higher impedance than the surrounding breast tissue, this spike in impedance is used to signal the presence of the calcifications, which are then sampled for examination by radiology.
ContributorsWen, Robert Bobby (Co-author) / Grula, Adam (Co-author) / Vergara, Marvin (Co-author) / Ramkumar, Shreya (Co-author) / Kozicki, Michael (Thesis director) / Ranjani, Kumaran (Committee member) / School of Molecular Sciences (Contributor) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
Breastfeeding has been shown by a number of studies to have numerous benefits on both the mother and the infant. Major health organizations such as the World Health Organization (WHO), now agree that breastfeeding should be encouraged and supported in all countries. But like many things, the wheels of the

Breastfeeding has been shown by a number of studies to have numerous benefits on both the mother and the infant. Major health organizations such as the World Health Organization (WHO), now agree that breastfeeding should be encouraged and supported in all countries. But like many things, the wheels of the law are slow to catch up with scientific evident. Although breastfeeding is supported, working women do not have the option of breastfeeding without consequences. For example, in 2003, Kirstie Marshall, a then member of parliament in Australia was ejected from the lower house chamber on February 23, for breastfeeding her baby [3]. According to standing order 30 at the time, "Unless by order of the House, no Member of this House shall presume to bring any stranger into any part of the House appropriated to the Members of this House while the House, or a Committee of the whole House, is sitting" [3]. The rules did not specify the age of strangers, so the then 11-day-old baby, Charlotte Louise and her mother were shown the exit door of parliament. She had to choose between being present at times of major discussions or leaving the house to breastfeed her child, she chose to leave. More recent statistics show that developed nations like the US and Australia which also have high rates of women employment had low rates of breastfeeding. This might mean that workplace policies do not favor breastfeeding or expressing milk at work. Fortunately, laws have since been introduced in both the United States and Australia that support breastfeeding at the workplace. The next step would be to access how these laws affect breastfeeding statistics and how variation between these two countries like the paid parental leave in Australia (which is not present in all US states) would affect these numbers.
ContributorsSakala, Lydia (Author) / Alison, Alison (Thesis director) / Reddy, Swapna (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
Ketone bodies are produced in the liver from the acetyl CoA derived from fatty acids that cannot enter the Krebs cycle. This is a sub-analysis of a larger study which had numerous outcome markers. This analysis focuses on the relationship between ketone blood levels and cognition. The study looked at

Ketone bodies are produced in the liver from the acetyl CoA derived from fatty acids that cannot enter the Krebs cycle. This is a sub-analysis of a larger study which had numerous outcome markers. This analysis focuses on the relationship between ketone blood levels and cognition. The study looked at the relationship between Time Restricted Feeding (TRF), a method of intermittent fasting. TRF is something that can be easily adapted into an individual’s lifestyle and has been shown to have multiple advantages. This 8-week study began with 23 enrolled participants, but due to COVID-19 only 11 participants could be tested for cognition and blood ketone levels after week 4. All participants had similar ranges of weight, height, age, BMI, hip, and waist measurements at baseline. Moreover, these demographic variables were not related to ketone levels or cognition. The data indicate that ketone bodies increased in participants practicing TRF and that the increase in ketone bodies in the blood, specifically β-hydroxybutyrate was strongly correlated to increased cognitive function. This is consistent with theories that elevated ketone levels allowed for early hunter-gather communities and other mammals to survive prolonged periods of nutrient deprivation while keeping high cognitive function.
ContributorsTaha, Basel Mahmoud (Author) / Johnston, Carol (Thesis director) / Karen, Sweazea (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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Description
The purpose of this thesis experiment was to design and create an Acoustically Active Cannula (AAC), which is furnished by a piezoelectric crystal placed at its tip that produces an acoustic navigation signal. I tested the functionality of the cannula in vitro and demonstrated its navigational abilities in vivo in

The purpose of this thesis experiment was to design and create an Acoustically Active Cannula (AAC), which is furnished by a piezoelectric crystal placed at its tip that produces an acoustic navigation signal. I tested the functionality of the cannula in vitro and demonstrated its navigational abilities in vivo in anesthetized pigs. This experiment was based upon ultrasound science and technology, and thus some practical experience with conventional (B-mode) and Doppler ultrasound was achieved as well. The results of bench and experimental animal studies indicated proper functionality of the AAC for identification and spatial navigation of its tip with color Doppler ultrasound imaging.
ContributorsShamsa, Kayvan (Author) / Tyler, William (Thesis director) / Belohlavek, Marek (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
The academic study of eSports, or professional competition through the medium of video games, has tended to focus on players' motivations to play and watch eSports as well as marketing concerns of huge eSports corporations. Instead of utilizing marketing or psychology to analyze this phenomenon, I investigate three areas of

The academic study of eSports, or professional competition through the medium of video games, has tended to focus on players' motivations to play and watch eSports as well as marketing concerns of huge eSports corporations. Instead of utilizing marketing or psychology to analyze this phenomenon, I investigate three areas of focus in accordance with available literature: the fans and their characteristics, the design of the game itself, and the relationship between fans and the game's developer. This investigation was conducted by first examining existing literature surrounding eSports fans, then collecting public domain data such as Reddit posts, forum posts, and YouTube videos, and last by studying interviews with developers and players. With this thesis, I apply a fan studies approach to eSports by creating a series of indicators based in each of the three focus areas which can be utilized as a systematic method of evaluating an eSport's popularity and growth.
ContributorsHilliker, Noah Henry (Author) / Ingram-Waters, Mary (Thesis director) / Schmidt, Peter (Committee member) / Anderson, Sky (Committee member) / School of Molecular Sciences (Contributor) / W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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DescriptionThis project is designed to generate enthusiasm for science among refugee students in hopes of inspiring them to continue learning science as well as to help them with their current understanding of their school science subject matter.
ContributorsSipes, Shannon Paige (Author) / O'Flaherty, Katherine (Thesis director) / Gregg, George (Committee member) / School of Molecular Sciences (Contributor) / Division of Teacher Preparation (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12