AI Article Synopsis
- A new method called PIX is introduced for measuring cellular velocity in small retinal blood vessels using adaptive optics, which analyzes pixel intensity profiles over time to assess flow direction.
- The method involves comparing each pixel’s intensity with others after a time shift to identify the most similar pixel, calculating the velocity by measuring displacement over time.
- PIX shows improved accuracy and efficiency in capturing flow dynamics compared to existing techniques like particle image velocimetry and manual tracking, demonstrating its potential in retinal studies.
Article Abstract
We present a new method for determining cellular velocity in the smallest retinal vascular networks as visualized with adaptive optics. The method operates by comparing the intensity profile of each movie pixel with that of every other pixel, after shifting in time by one frame. The time-shifted pixel which most resembles the reference pixel is deemed to be a 'source' or 'destination' of flow information for that pixel. Velocity in the transverse direction is then calculated by dividing the spatial displacement between the two pixels by the inter-frame period. We call this method pixel intensity cross-correlation, or "PIX". Here we compare measurements derived from PIX to two other state-of-the-art algorithms (particle image velocimetry and the spatiotemporal kymograph), as well as to manually tracked cell data. The examples chosen highlight the potential of the new algorithm to substantially improve spatial and temporal resolution, resilience to noise and aliasing, and assessment of network flow properties compared with existing methods.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6592569 | PMC |
| http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0218918 | PLOS |
Publication Analysis
Top Keywords
Similar Publications
Automatic Optical Path Alignment Method for Optical Biological Microscope.
Sensors (Basel)
December 2024
Guangxi Key Laboratory of Machine Vision and Intelligent Control, Wuzhou University, Wuzhou 543000, China.
A high-quality optical path alignment is essential for achieving superior image quality in optical biological microscope (OBM) systems. The traditional automatic alignment methods for OBMs rely heavily on complex masker-detection techniques. This paper introduces an innovative, image-sensor-based optical path alignment approach designed for low-power objective (specifically 4×) automatic OBMs.
View Article and Find Full Text PDFA computer vision model for the identification and scoring of calcium in aortic valve stenosis: a single-center experience.
Cardiovasc Diagn Ther
December 2024
East Slovak Institute of Cardiovascular Diseases and School of Medicine, Pavol Jozef Safarik University, Kosice, Slovakia.
Background: Echocardiography is widely used to assess aortic stenosis (AS) but can yield inconsistent results, leading to uncertainty about AS severity and the need for further diagnostics. This retrospective study aimed to evaluate a novel echocardiography-based marker, the signal intensity coefficient (SIC), for its potential in accurately identifying and quantifying calcium in AS, enhancing noninvasive diagnostic methods.
Methods: Between May 2022 and October 2023, 112 cases of AS that were previously considered severe by echocardiography were retrospectively evaluated, as well as a group of 50 cases of mild or moderate AS, both at the Eastern Slovak Institute of Cardiovascular Diseases in Kosice, Slovakia.
Alterations in the uterine echotexture, hemodynamics, and histological findings in relation to metabolomic profiles in goats with different ovarian activities (active versus inactive ovaries).
Vet Res Commun
January 2025
Laboratory of Veterinary Physiology, Department of Veterinary Medicine, Faculty of Agriculture, Tokyo University of Agriculture and Technology, 3-5-8 Saiwai-Cho, 183-8509, Fuchu, Tokyo, Japan.
This study investigated, for the first time, the alterations in the uterine echotexture and blood flow in cyclic and acyclic (inactive ovary) goats using ultrasonography. The study aimed also to evaluate the metabolomic changes in the plasma of cyclic and acyclic goats. Furthermore, the histopathological approach was applied to the specimens of the uterus to validate the findings of this study.
View Article and Find Full Text PDFAtmospheric Pressure Mass Spectrometry Imaging Using Electrospray-Assisted Laser Desorption/Ionization with Gas Transportation through a Heated Tube and Minimal Sample Preparation.
Mass Spectrom (Tokyo)
December 2024
Graduate School of Engineering, Osaka University, A1/A14, 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan.
Mass spectrometry (MS) is a valuable tool that enables label-free analysis and the ability to measure multiple molecules. The atmospheric pressure MS imaging (MSI) method usually requires tedious sample preparation. A simple ionization method with minimal sample preparation is needed for high-throughput analysis.
View Article and Find Full Text PDFDeep learning-based encryption scheme for medical images using DCGAN and virtual planet domain.
Sci Rep
January 2025
Department of Computer Science and Information Systems, Birla Institute of Technology and Science-Pilani, Hyderabad Campus, Hyderabad, 500078, India.
The motivation for this article stems from the fact that medical image security is crucial for maintaining patient confidentiality and protecting against unauthorized access or manipulation. This paper presents a novel encryption technique that integrates the Deep Convolutional Generative Adversarial Networks (DCGAN) and Virtual Planet Domain (VPD) approach to enhance the protection of medical images. The method uses a Deep Learning (DL) framework to generate a decoy image, which forms the basis for generating encryption keys using a timestamp, nonce, and 1-D Exponential Chebyshev map (1-DEC).
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!