A5079492567- Medical Image Segmentation Techniques
- Radiomics and Machine Learning in Medical Imaging
- Image Retrieval and Classification Techniques
- Medical Imaging and Analysis
- Advanced Measurement and Metrology Techniques
- AI in cancer detection
- 3D Shape Modeling and Analysis
- Image Processing and 3D Reconstruction
- Industrial Vision Systems and Defect Detection
- Reinforcement Learning in Robotics
- Machine Learning in Materials Science
- High Entropy Alloys Studies
- Hate Speech and Cyberbullying Detection
- Pulmonary Hypertension Research and Treatments
- Advanced Neuroimaging Techniques and Applications
- Advanced machining processes and optimization
- Interpreting and Communication in Healthcare
- Plant Water Relations and Carbon Dynamics
- Neural Networks and Applications
- Supply Chain and Inventory Management
- Scheduling and Timetabling Solutions
- Chalcogenide Semiconductor Thin Films
- Fluid Dynamics and Vibration Analysis
- Cardiac Valve Diseases and Treatments
- Advanced Surface Polishing Techniques
University of Utah
2022-2024
Advanced Imaging Research (United States)
2024
Mitsubishi Heavy Industries (Germany)
2017
We introduce Llama Guard, an LLM-based input-output safeguard model geared towards Human-AI conversation use cases. Our incorporates a safety risk taxonomy, valuable tool for categorizing specific set of risks found in LLM prompts (i.e., prompt classification). This taxonomy is also instrumental classifying the responses generated by LLMs to these prompts, process we refer as response classification. For purpose both and classification, have meticulously gathered dataset high quality....
Anatomy evaluation is crucial for understanding the physiological state, diagnosing abnormalities, and guiding medical interventions. Statistical shape modeling (SSM) vital in this process. By enabling extraction of quantitative morphological descriptors from MRI CT scans, SSM provides comprehensive descriptions anatomical variations within a population. However, effectiveness anatomy hinges on quality robustness models. While deep learning techniques show promise addressing these challenges...
Statistical shape modeling (SSM) is a valuable and powerful tool to generate detailed representation of complex anatomy that enables quantitative analysis shapes their variations. SSM applies mathematics, statistics, computing parse the into some (such as correspondence points or landmarks) which can be used study covariance patterns answer various questions about anatomical variations across population. Complex structures have many diverse parts with varying interactions intricate...
Transient growth of perturbations by linear non-modal evolution is studied here in a stably stratified bounded Couette flow. The density stratification linear. Classical inviscid stability theory states that parallel shear flow stable to exponential disturbances if the Richardson number (Ri) greater than 1/4 everywhere Experiments and numerical simulations at higher Ri show however algebraically growing can lead transient amplification. complexity stems from its ability combine this...
Statistical shape modeling (SSM) is a powerful computational framework for quantifying and analyzing the geometric variability of anatomical structures, facilitating advancements in medical research, diagnostics, treatment planning. Traditional methods from imaging data demand significant manual resources. Additionally, these necessitate repeating entire pipeline to derive descriptors (e.g., surface-based point correspondences) new data. While deep learning approaches have shown promise...
Image registration is a core task in computational anatomy that establishes correspondences between images. Invertible deformable registration, which computes deformation field and handles complex, non-linear transformation, essential for tracking anatomical variations, especially neuroimaging applications where inter-subject differences longitudinal changes are key. Analyzing the fields challenging due to their non-linearity, limiting statistical analysis. However, traditional approaches...
Anatomical shape analysis plays a pivotal role in clinical research and hypothesis testing, where the relationship between form function is paramount. Correspondence-based statistical modeling (SSM) facilitates population-level morphometrics but requires cumbersome, potentially bias-inducing construction pipeline. Recent advancements deep learning have streamlined this process inference by providing SSM prediction directly from unsegmented medical images. However, proposed approaches are...
Red teaming assesses how large language models (LLMs) can produce content that violates norms, policies, and rules set during their safety training. However, most existing automated methods in the literature are not representative of way humans tend to interact with AI models. Common users may have advanced knowledge adversarial machine learning or access model internals, they do spend a lot time crafting single highly effective prompt. Instead, likely make use techniques commonly shared...
Introduction: Myriad disorders cause right ventricular (RV) dilation and lead to tricuspid regurgitation (TR). Because the thin-walled, flexible RV is mechanically coupled pulmonary circulation left septum, it distorts with any disturbance in cardiopulmonary system. TR, therefore, can result from hypertension, heart failure, or intrinsic dysfunction; but once occurs, TR initiates a cycle of worsening volume overload, potentially progressing failure. Characteristic three-dimensional...
Strategic workforce planning has become increasing essential for modern organisations. It is the key approach used by organisation to improve and maintain capabilities of its workforce. However many experts distinguish between Training Development, being that training tends be more closely focused adapted demands short-term performance concerns, while development towards expanding an individual skills future responsibilities. Enhancement through programmes leads different results. The...
The internal gear grinding machine, ZI20A is the first of its kind that applicable for mass production gears. It suitable planetary gears, heat-treated or external gears at high speeds with accuracy. One features this machine ability to grind stepped workpieces. In case workpieces, it difficult determine axial stroke required achieve proper entire tooth surface without causing any interference region parts wheel. During test such sometimes flank remains unground ends due inadequate stroke. A...
This paper presents a hi-speed vision based gear grinding surface inspector for industrial use. In recent years, with the widespread use of machine, new ghost noises have appeared. Such are derived from periodic undulations which cannot be detected by using traditional probing method. For detection undulation, this research adopts line laser to convert topography into observable images and an image processing method analyse reflected pattern in image. reports design process on-machine...