Multi-modal and multi-dimensional biomedical image data analysis using deep learning

There is a growing need for the development of computational methods and tools for automated, objective, and quantitative analysis of biomedical signal and image data to facilitate disease and treatment monitoring, early diagnosis, and scientific discovery. Recent advances in artificial intelligence and machine learning, particularly in deep learning, have revolutionized computer vision and image analysis for many application areas. While processing of non-biomedical signal, image, and video data using deep learning methods has been very successful, high-stakes biomedical applications present unique challenges such as different image modalities, limited training data, need for explainability and interpretability etc. that need to be addressed. In this dissertation, we developed novel, explainable, and attention-based deep learning frameworks for objective, automated, and quantitative analysis of biomedical signal, image, and video data. The proposed solutions involve multi-scale signal analysis for oraldiadochokinesis studies; ensemble of deep learning cascades using global soft attention mechanisms for segmentation of meningeal vascular networks in confocal microscopy; spatial attention and spatio-temporal data fusion for detection of rare and short-term video events in laryngeal endoscopy videos; and a novel discrete Fourier transform driven class activation map for explainable-AI and weakly-supervised object localization and segmentation for detailed vocal fold motion analysis using laryngeal endoscopy videos. Experiments conducted on the proposed methods showed robust and promising results towards automated, objective, and quantitative analysis of biomedical data, that is of great value for potential early diagnosis and effective disease progress or treatment monitoring.Includes bibliographical references

Models and Analysis of Vocal Emissions for Biomedical Applications

The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies

Models and Analysis of Vocal Emissions for Biomedical Applications

The International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA) came into being in 1999 from the particularly felt need of sharing know-how, objectives and results between areas that until then seemed quite distinct such as bioengineering, medicine and singing. MAVEBA deals with all aspects concerning the study of the human voice with applications ranging from the neonate to the adult and elderly. Over the years the initial issues have grown and spread also in other aspects of research such as occupational voice disorders, neurology, rehabilitation, image and video analysis. MAVEBA takes place every two years always in Firenze, Italy. This edition celebrates twenty years of uninterrupted and succesfully research in the field of voice analysis

Learning Disabilities

Learning disabilities are a heterogeneous group of disorders characterized by failure to acquire, retrieve, and use information competently. These disorders have a multifactorial aetiology and are most common and severe in children, especially when comorbid with other chronic health conditions. This book provides current and comprehensive information about learning disorders, including information on neurobiology, assessment, clinical features, and treatment. Chapters cover such topics as historical research and hypotheses of learning disorders, neuropsychological assessment and counselling, characteristics of specific disorders such as autism and ADHD, evidence-based treatment strategies and assistive technologies, and much more

Effects of dual-task functional power training on cognitive function, well-being and inflammatory and neurological markers in older adults

This thesis found that a 26 week dual-task functional power training program improved several aspects of cognition, lower limb muscle power and function, and mobility in independently living older adults. However the intervention had no effect on circulating levels of inflammatory or neurological markers, with minimal benefits for well-being

Effects of Diversity and Neuropsychological Performance in an NFL Cohort

Objective: The aim of this study was to examine the effect of ethnicity on neuropsychological test performance by comparing scores of white and black former NFL athletes on each subtest of the WMS. Participants and Methods: Data was derived from a de-identified database in South Florida consisting of 63 former NFL white (n=28, 44.4%) and black (n=35, 55.6%) athletes (Mage= 50.38; SD= 11.57). Participants completed the following subtests of the WMS: Logical Memory I and II, Verbal Paired Associates I and II, and Visual Reproduction I and II. Results: A One-Way ANOVA yielded significant effect between ethnicity and performance on several subtests from the WMS-IV. Black athletes had significantly lower scores compared to white athletes on Logical Memory II: F(1,61) = 4.667, p= .035, Verbal Paired Associates I: F(1,61) = 4.536, p = .037, Verbal Paired Associates: II F(1,61) = 4.677, p = .034, and Visual Reproduction I: F(1,61) = 6.562, p = .013. Conclusions: Results suggest significant differences exist between white and black athletes on neuropsychological test performance, necessitating the need for proper normative samples for each ethnic group. It is possible the differences found can be explained by the psychometric properties of the assessment and possibility of a non-representative sample for minorities, or simply individual differences. Previous literature has found white individuals to outperform African-Americans on verbal and non-verbal cognitive tasks after controlling for socioeconomic and other demographic variables (Manly & Jacobs, 2002). This highlights the need for future investigators to identify cultural factors and evaluate how ethnicity specifically plays a role on neuropsychological test performance. Notably, differences between ethnic groups can have significant implications when evaluating a sample of former athletes for cognitive impairment, as these results suggest retired NFL minorities may be more impaired compared to retired NFL white athletes

Distinguishing Performance on Tests of Executive Functions Between Those with Depression and Anxiety

Objective: To see if there are differences in executive functions between those diagnosed with Major Depressive Disorder (MDD) and those with Generalized Anxiety Disorder (GAD).Participants and Methods: The data were chosen from a de-identified database at a neuropsychological clinic in South Florida. The sample used was adults diagnosed with MDD (n=75) and GAD (n=71) and who had taken the Halstead Category Test, Trail Making Test, Stroop Test, and the Wisconsin Card Sorting Test. Age (M=32.97, SD=11.75), gender (56.7% female), and race (52.7% White) did not differ between groups. IQ did not differ but education did (MDD=13.41 years, SD=2.45; GAD=15.11 years, SD=2.40), so it was ran as a covariate in the analyses. Six ANCOVAs were run separately with diagnosis being held as the fixed factor and executive function test scores held as dependent variables. Results: The MDD group only performed worse on the Category Test than the GAD group ([1,132]=4.022, p\u3c .05). Even though both WCST scores used were significantly different between the two groups, both analyses failed Levene’s test of Equality of Error Variances, so the data were not interpreted. Conclusions: Due to previous findings that those diagnosed with MDD perform worse on tests of executive function than normal controls (Veiel, 1997), this study wanted to compare executive function performance between those diagnosed with MDD and those with another common psychological disorder. The fact that these two groups only differed on the Category Test shows that there may not be much of a difference in executive function deficits between those with MDD and GAD. That being said, not being able to interpret the scores on the WCST test due to a lack of homogeneity of variance indicates that a larger sample size is needed to compare these two types of patients, as significant differences may be found. The results of this specific study, however, could mean that the Category Test could be used in assisting the diagnosis of a MDD patient

The Effect of Ethnicity on Neuropsychological Test Performance of Former NFL Athletes

Objective: To investigate the effect of ethnicity on neuropsychological test performance by specifically exploring differences between white and black former NFL athletes on subtests of the WAIS-IV. Participants and Methods: Data was derived from a de-identified database in Florida consisting of 63 former NFL athletes (Mage=50.38; SD=11.57); 28 white and 35 black. Participants completed the following subtests of the WAIS-IV: Block Design, Similarities, Digit Span, Matrix Reasoning, Arithmetic, Symbol Search, Visual Puzzles, Coding, and Cancellation. Results: One-Way ANOVA yielded a significant effect between ethnicity and performance on several subtests. Black athletes had significantly lower scaled scores than white athletes on Block Design F(1,61)=14.266, p\u3c.001, Similarities F(1,61)=5.904, p=.018, Digit Span F(1,61)=8.985, p=.004, Arithmetic F(1,61)=16.07, p\u3c.001 and Visual Puzzles F(1,61)=16.682, p\u3c .001. No effect of ethnicity was seen on performance of Matrix Reasoning F(1,61)=2.937, p=.092, Symbol Search F(1,61)=3.619, p=.062, Coding F(1,61)=3.032, p=.087 or Cancellation F(1,61)=2.289, p=.136. Conclusions: Results reveal significant differences between white and black athletes on all subtests of the WAIS-IV but those from the Processing Speed Scale and Matrix Reasoning. These findings align with previous literature that found white individuals to outperform African-Americans on verbal and non-verbal tasks after controlling for socioeconomic and demographic variables (Manly & Jacobs, 2002). These differences may also be a reflection of the WAIS-IV’s psychometric properties and it is significant to consider the normative sample used may not be appropriate for African-Americans. This study highlights the need for future research to identify how ethnicity specifically influences performance, sheds light on the importance of considering cultural factors when interpreting test results, and serves as a call to action to further understand how and why minorities may not be accurately represented in neuropsychological testing

Regional Cerebral Blood Flow Patterns in Children vs. Adults with ADHD Combined and Inattentive Types: A SPECT Study

Objective: The current study sought to determine whether ADHD Combined Type (ADHD-C) and ADHD Primarily Inattentive Type (ADHD-PI) showed differential regional cerebral blood flow (rCBF) patterns in children vs. adults. Participants and Methods: The overall sample (N=1484) was effectively split into four groups: adults with ADHD-PI (n=519), adults with ADHD-C (n=405), children with ADHD-PI (n=192), children with ADHD-C (n=368). All participants were void of bipolar, schizophrenia, autism, neurocognitive disorders, and TBI. The data were collected from a de-identified archival database of individuals who underwent SPECT scans at rest. Results: Using αConclusions: Overall, the current study suggested that children may show rCBF differences between different ADHD subtypes, but adults may not. The current study did not find significance in any of the 17 brain regions examined when comparing adults with ADHD-C to adults with ADHD-PI. All significant findings were attributed to the children with ADHD-C group showing aberrant blood flow rate than at least one other group. Previous research has supported that the differentiation of these subtypes as distinctive disorders is difficult to make in adults (Sobanski et al., 2006). Other research has indicated the potential of imaging techniques to differentiate the two in children (Al-Amin, Zinchenko, & Geyer, 2018). The current findings support nuanced ways in which rCBF patterns of ADHD-C and ADHD-PI differ between children and adults