Vision Science Commons^™

Vergence Task-Based Neural Pathways With Binocularly Normal Vision And Comorbid Persistent Post-Concussive Symptoms -Convergence Insufficiency, Ayushi Sangoi

Dissertations

Binocular dysfunctions are more prevalent in the persistent post-concussive symptoms (PPCS) population than in the general population. The most prevalent binocular disorder is convergence insufficiency (CI), affecting 3-17% of the general population and up to 10 times as many people with PPCS. CI makes it difficult to fuse or maintain fusion on targets at near, and its symptoms include double or blurry vision and headaches when performing close-range tasks such as reading, which can exacerbate PPCS symptoms. Given controversy over the subjectivity and effectiveness of diagnostic tools and symptom surveys for both PPCS and CI, understanding why CI has high …

Adversarial Robustness In Biomedical Time-Series Models, Rohan Tiwari

Bioengineering Theses

This study investigates adversarial vulnerabilities in deep learning models for biomedical time-series classification across two clinically important modalities: electrocardiography (ECG) and electroencephalography (EEG). Using the MIT-BIH Arrhythmia and CHB-MIT seizure datasets, I evaluate time-domain attacks (FGSM, PGD), Fourier-domain constrained attacks, and learned spectral perturbations designed to reveal modality-specific sensitivity patterns. Across both tasks, a consistent trend emerges low-frequency components (0–5 Hz) constitute a dominant axis of adversarial vulnerability, with perturbations in this range producing the steepest degradation in classification performance. In ECG models, protecting the physiologically relevant QRS band (5–20 Hz) significantly improves robustness, whereas EEG models remain highly sensitive …

Structured Light Radial-View Endoscope Imaging Development For Evaluation Of Human Tissue, Xiyan Li

McKelvey School of Engineering Graduate Student Theses & Dissertations

In this thesis, we improved an existing structured light methodology to more accurately estimate tissue optical properties imaged in a single snapshot. The developed approach is a major enhancement of the traditional three-phase spatial frequency domain imaging system: It greatly simplifies the operational procedure while also maintaining high accuracy in optical property measurements .

Leveraging this improved approach, we have developed a low-cost, compact, and radial-view endoscope prototype. This prototype combines affordability with high functionality and a user-friendly design. To assess the performance and reliability of our endoscope, we conducted comprehensive evaluations involving tissue-mimicking phantoms, as well as ex vivo …

Implementing Unmanned Aerial Vehicles To Collect Human Gait Data At Distance And Altitude For Identification And Re-Identification, Donn E. Bartram

Graduate Theses, Dissertations, and Problem Reports (ETD)

Gait patterns are a class of biometric information pertaining to the way a person moves and poses. Gait information is unique to each person and can be used to identify and reidentify people. Historically, this task has been achieved through the use of multiple ground-based imaging sensors. However, as Unmanned Aerial Vehicles (UAVs) advance, they present the opportunity to evolve the process of persons identification and re-identification. Collecting human gait data using UAVs at distances ranging from 20m to 500m and altitudes ranging from 0m to 120m is a challenging task. The current biometric data collection methods, primarily designed for …

Deutj: An Imagej Plugin For Improved Automatic Masking And Segmentation Of Images From Confocal Microscopy, Sunny Cui

Independent Student Projects and Publications

Due to advances in microscopic imaging, there are a plethora of biological molecules that can now be tagged and subsequentially imaged from almost any cell, organism, or tissue. However, the ability of software to analyze these images remains to be a challenge. ImageJ is open source software that allows for the processing of these images, but faces challenges when dealing with images that show weak contrast between objects of interest and background. DeutJ is an ImageJ plugin that color corrects and brightness corrects gradients that inhibit segmentation in confocal microscopy images. It can analyze hundreds of images from a given …

Development Of Light Actuated Chemical Delivery Platform On A 2-D Array Of Micropore Structure, Hojjat Rostami Azmand, Hojjat Rostami Azmand

Dissertations and Theses

Localized chemical delivery plays an essential role in the fundamental information transfers within biological systems. Thus, the ability to mimic the natural chemical signal modulation would provide significant contributions to understand the functional signaling pathway of biological cells and develop new prosthetic devices for neurological disorders. In this paper, we demonstrate a light-controlled hydrogel platform that can be used for localized chemical delivery in a high spatial resolution. By utilizing the photothermal behavior of graphene-hydrogel composites confined within micron-sized fluidic channels, patterned light illumination creates the parallel and independent actuation of chemical release in a group of fluidic ports. The …

Bibliometric Review On Liver And Tumour Segmentation Using Deep Learning, Jayant Jagtap, Aamir Habeeb, Avinash Jha, Shrey Aggarwal, Khushi Gupta

Library Philosophy and Practice (e-journal)

One of the major organs in the body is liver where tumors occur often. Malignant liver tumors pose a serious hazard to human life and health. Manual segmentation of the liver organ and tumor from computed tomography (CT) scans is difficult, time-consuming, and skewed to the clinician's experience, yet it is essential for hepatic surgical planning. However, due to the following considerations, segmenting liver tumors from computed tomography (CT) images is difficult: In CT pictures, the contrast between the liver tumor and healthy tissues is low, and the boundary is indistinct; the picture of the liver tumor is confusing, with …

When The Brain Plays A Game: Neural Responses To Visual Dynamics During Naturalistic Visual Tasks, Jason Ki

Dissertations and Theses

Many day-to-day tasks involve processing of complex visual information in a continuous stream. While much of our knowledge on visual processing has been established from reductionist approaches in lab-controlled settings, very little is known about the processing of complex dynamic stimuli experienced in everyday scenarios. Traditional investigations employ event-related paradigms that involve presentation of simple stimuli at select locations in visual space and discrete moments in time. In contrast, visual stimuli in real-life are highly dynamic, spatially-heterogeneous, and semantically rich. Moreover, traditional experiments impose unnatural task constraints (e.g., inhibited saccades), thus, it is unclear whether theories developed under the reductionist …

Network-Level Mechanisms Underlying Effects Of Transcranial Direct Current Stimulation (Tdcs) On Visuomotor Learning, Pejman Sehatpour, Clément Dondé, Matthew J. Hoptman, Johanna Kreither, Devin Adair, Elisa Dias, Blair Vail, Stephanie Rohrig, Gail Silipo, Javier Lopez-Calderon, Antigona Martinez, Daniel C. Javitt

Publications and Research

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation approach in which low level currents are administered over the scalp to influence underlying brain function. Prevailing theories of tDCS focus on modulation of excitation-inhibition balance at the local stimulation location. However, network level effects are reported as well, and appear to depend upon differential underlying mechanisms. Here, we evaluated potential network-level effects of tDCS during the Serial Reaction Time Task (SRTT) using convergent EEG- and fMRI-based connectivity approaches. Motor learning manifested as a significant (p <.0001) shift from slow to fast responses and corresponded to a significant increase in beta-coherence (p <.0001) and fMRI connectivity (p <.01) particularly within the visual-motor pathway. Differential patterns of tDCS effect were observed within different parametric task versions, consistent with network models. Overall, these findings demonstrate objective physiological effects of tDCS at the network level that result in effective behavioral modulation when tDCS parameters are matched to network-level requirements of the underlying task.

Noncontact Multiscale Diffuse Optical Imaging Of Deep Tissue Hemodynamics In Animals And Humans, Siavash Mazdeyasna

Theses and Dissertations--Biomedical Engineering

Blood flow (BF) impacts the delivery of oxygen and nutrients to tissues and the removal of metabolic byproducts from tissues. Imaging of BF distributions helps characterize many diseases associated with tissue hypoxia/ischemia. The purpose of this study was to develop and validate a novel, noninvasive, noncontact, high-density camera-based speckle contrast diffuse correlation tomography (scDCT) device for use in both animal and human studies. The scDCT uses a galvo-mirror to remotely deliver the focused point near-infrared light to source positions and a sensitive 2D camera to quantify spatial diffuse speckle fluctuations, resulting from the movement of red blood cells in deep …

Vector Flow Imaging In Pediatric Cardiology - Extracting And Validating Data, Mason Belue

Biomedical Engineering Undergraduate Honors Theses

In the field of bedside cardiac diagnostic imaging, Doppler Ultrasound (DU) is the gold standard for diagnosing heart conditions. The largest benefit of DU is its ability to noninvasively image cardiac flow and allow the estimation of blood velocity and quantification of anatomical disease. However, to get correct velocity estimation, the position of the transducer in relation to the flow field needs to be known. This is the problem of angle/direction dependency and limits DUs accuracy when imaging in areas where perfect alignment or exact position of the transducer in relation to flow field is not possible or known, such …

Seeing Eye To Eye: A Machine Learning Approach To Automated Saccade Analysis, Maigh Attre

Honors Scholar Theses

Abnormal ocular motility is a common manifestation of many underlying pathologies particularly those that are neurological. Dynamics of saccades, when the eye rapidly changes its point of fixation, have been characterized for many neurological disorders including concussions, traumatic brain injuries (TBI), and Parkinson’s disease. However, widespread saccade analysis for diagnostic and research purposes requires the recognition of certain eye movement parameters. Key information such as velocity and duration must be determined from data based on a wide set of patients’ characteristics that may range in eye shapes and iris, hair and skin pigmentation [36]. Previous work on saccade analysis has …

Towards Omni-Tomography -- Grand Fusion Of Multiple Modalities For Simultaneous Interior Tomography, Ge Wang, Jie Zhang, Hao Gao, Victor Weir, Hengyong Yu, Wenxiang Cong, Xiaochen Xu, Haiou Shen, James Bennett, Mark Furth, Yue Wang, Michael Vannier

Radiology Faculty Publications

We recently elevated interior tomography from its origin in computed tomography (CT) to a general tomographic principle, and proved its validity for other tomographic modalities including SPECT, MRI, and others. Here we propose "omni-tomography", a novel concept for the grand fusion of multiple tomographic modalities for simultaneous data acquisition in a region of interest (ROI). Omni-tomography can be instrumental when physiological processes under investigation are multi-dimensional, multi-scale, multi-temporal and multi-parametric. Both preclinical and clinical studies now depend on in vivo tomography, often requiring separate evaluations by different imaging modalities. Over the past decade, two approaches have been used for multimodality …