arXiv subjects

Preeti Verma

Publications and source records attributed to Preeti Verma.

4 recordsLinked to original sources

arXiv2026

On the Modeling of Kink Oscillations in Fine-Structured Coronal Loops with Field-aligned Nonlinear Longitudinal Disturbances

We investigate the influence of nonlinear longitudinal disturbances, triggered by an initial field-aligned velocity flow, on the damping of standing kink oscillations in fine-structured, cool coronal loop strands under isobaric conditions. Using two-dimensional ideal MHD simulations, we model different realistic flow geometries, bounded, unbounded, and external, and quantify their impact on wave excitation, damping, and energy leakage. Our modelled loop strand incorporates strong density contrasts ($d = 5$ and $d = 20$), providing a configuration consistent with cool-loop observations from Hinode/SOT and SDO/AIA. Our results show that while the nonlinear disturbances exert mild influence on the oscillation period, they substantially modify the damping time. Unbounded flows yield the strongest damping, reducing the damping time by up to $\sim 25\%$ compared to bounded flows, caused by enhanced wave-flow coupling and scattering. Longitudinally inhomogeneous flows further intensify the damping, with high-density strands exhibiting faster convergence toward the uniform-flow limit. In cases with supersonic internal flow, slow sausage-mode harmonics and weak slow shocks are additionally excited, indicating the generation of mixed-mode wave responses in flow-dominated loops. These findings demonstrate that realistic, spatially extended nonlinear disturbances play a significant role in the damping of kink oscillations and should be incorporated into forward modeling and coronal seismology diagnostics.

astro-ph.SR↗

arXiv2024

Fr\'echet Radiomic Distance (FRD): A Versatile Metric for Comparing Medical Imaging Datasets

Determining whether two sets of images belong to the same or different distributions or domains is a crucial task in modern medical image analysis and deep learning; for example, to evaluate the output quality of image generative models. Currently, metrics used for this task either rely on the (potentially biased) choice of some downstream task, such as segmentation, or adopt task-independent perceptual metrics (e.g., Fr\'echet Inception Distance/FID) from natural imaging, which we show insufficiently capture anatomical features. To this end, we introduce a new perceptual metric tailored for medical images, FRD (Fr\'echet Radiomic Distance), which utilizes standardized, clinically meaningful, and interpretable image features. We show that FRD is superior to other image distribution metrics for a range of medical imaging applications, including out-of-domain (OOD) detection, the evaluation of image-to-image translation (by correlating more with downstream task performance as well as anatomical consistency and realism), and the evaluation of unconditional image generation. Moreover, FRD offers additional benefits such as stability and computational efficiency at low sample sizes, sensitivity to image corruptions and adversarial attacks, feature interpretability, and correlation with radiologist-perceived image quality. Additionally, we address key gaps in the literature by presenting an extensive framework for the multifaceted evaluation of image similarity metrics in medical imaging -- including the first large-scale comparative study of generative models for medical image translation -- and release an accessible codebase to facilitate future research. Our results are supported by thorough experiments spanning a variety of datasets, modalities, and downstream tasks, highlighting the broad potential of FRD for medical image analysis.

cs.CV↗

arXiv2024

Towards Learning Contrast Kinetics with Multi-Condition Latent Diffusion Models

Contrast agents in dynamic contrast enhanced magnetic resonance imaging allow to localize tumors and observe their contrast kinetics, which is essential for cancer characterization and respective treatment decision-making. However, contrast agent administration is not only associated with adverse health risks, but also restricted for patients during pregnancy, and for those with kidney malfunction, or other adverse reactions. With contrast uptake as key biomarker for lesion malignancy, cancer recurrence risk, and treatment response, it becomes pivotal to reduce the dependency on intravenous contrast agent administration. To this end, we propose a multi-conditional latent diffusion model capable of acquisition time-conditioned image synthesis of DCE-MRI temporal sequences. To evaluate medical image synthesis, we additionally propose and validate the Fr\'echet radiomics distance as an image quality measure based on biomarker variability between synthetic and real imaging data. Our results demonstrate our method's ability to generate realistic multi-sequence fat-saturated breast DCE-MRI and uncover the emerging potential of deep learning based contrast kinetics simulation. We publicly share our accessible codebase at https://github.com/RichardObi/ccnet and provide a user-friendly library for Fr\'echet radiomics distance calculation at https://pypi.org/project/frd-score.

eess.IV↗

arXiv2013

Punjabi Language Interface to Database: a brief review

Unlike most user-computer interfaces, a natural language interface allows users to communicate fluently with a computer system with very little preparation. Databases are often hard to use in cooperating with the users because of their rigid interface. A good NLIDB allows a user to enter commands and ask questions in native language and then after interpreting respond to the user in native language. For a large number of applications requiring interaction between humans and the computer systems, it would be convenient to provide the end-user friendly interface. Punjabi language interface to database would proof fruitful to native people of Punjab, as it provides ease to them to use various e-governance applications like Punjab Sewa, Suwidha, Online Public Utility Forms, Online Grievance Cell, Land Records Management System,legacy matters, e-District, agriculture, etc. Punjabi is the mother tongue of more than 110 million people all around the world. According to available information, Punjabi ranks 10th from top out of a total of 6,900 languages recognized internationally by the United Nations. This paper covers a brief overview of the Natural language interface to database, its different components, its advantages, disadvantages, approaches and techniques used. The paper ends with the work done on Punjabi language interface to database and future enhancements that can be done.

cs.CL↗