Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Variance01:15

Variance

12.4K
The deviations show how spread out the data are about the mean. A positive deviation occurs when the data value exceeds the mean, whereas a negative deviation occurs when the data value is less than the mean. If the deviations are added, the sum is always zero. So one cannot simply add the deviations to get the data spread. By squaring the deviations, the numbers are made positive; thus, their sum will also be positive.
The standard deviation measures the spread in the same units as the data....
12.4K
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

510
Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
510
Nuclear Stability03:18

Nuclear Stability

23.3K
Protons and neutrons, collectively called nucleons, are packed together tightly in a nucleus. With a radius of about 10−15 meters, a nucleus is quite small compared to the radius of the entire atom, which is about 10−10 meters. Nuclei are extremely dense compared to bulk matter, averaging 1.8 × 1014 grams per cubic centimeter. If the earth’s density were equal to the average nuclear density, the earth’s radius would be only about 200 meters.
To hold positively charged protons together...
23.3K
RNA Stability01:53

RNA Stability

35.8K
Intact DNA strands can be found in fossils, while scientists sometimes struggle to keep RNA intact under laboratory conditions. The structural variations between RNA and DNA underlie the differences in their stability and longevity. Because DNA is double-stranded, it is inherently more stable. The single-stranded structure of RNA is less stable but also more flexible and can form weak internal bonds. Additionally, most RNAs in the cell are relatively short, while DNA can be up to 250 million...
35.8K
Stability01:28

Stability

421
The time response of a linear time-invariant (LTI) system can be divided into transient and steady-state responses. The transient response represents the system's initial reaction to a change in input and diminishes to zero over time. In contrast, the steady-state response is the behavior that persists after the transient effects have faded.
The stability of an LTI system is determined by the roots of its characteristic equation, known as poles. A system is stable if it produces a bounded...
421
Stability of structures01:14

Stability of structures

531
In mechanical engineering, the stability of systems under various forces is critical for designing durable and efficient structures. One fundamental way to explore these concepts is by analyzing systems like two rods connected at a pivot point, O, with a torsional spring of spring constant k at the pivot point. This system is similar in appearance to a scissor jack used to change tires on a car. In this case, the arms of the linkage (equivalent to the rods in this system) are entirely vertical,...
531

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Multimodal clinical data integration for prognosis of pulmonary embolism: A comparative study.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026
Same author

Handling missing modalities in multimodal survival prediction for non-small cell lung cancer.

NPJ digital medicine·2026
Same author

Predicting 2-Year Overall Survival in NSCLC from CT Scans Using 2D CNNs and Soft Attention.

Studies in health technology and informatics·2026
Same author

Machine-Learning-Based Color Sensing Using Wearable SENSIPATCH Spectrometer Module: An Experimental Study.

Sensors (Basel, Switzerland)·2026
Same author

Development and internal validation of mammography feature-based prognostic models for distant recurrence-free survival of invasive breast cancer in a screening cohort.

NPJ breast cancer·2026
Same author

Latent diffusion autoencoders: Toward efficient and meaningful unsupervised representation learning in medical imaging - a case study on Alzheimer's disease.

Medical image analysis·2026

Related Experiment Video

Updated: Feb 8, 2026

Calcification of Vascular Smooth Muscle Cells and Imaging of Aortic Calcification and Inflammation
08:43

Calcification of Vascular Smooth Muscle Cells and Imaging of Aortic Calcification and Inflammation

Published on: May 31, 2016

20.4K

Improving the Automated Detection of Calcifications Using Adaptive Variance Stabilization.

Alessandro Bria, Claudio Marrocco, Lucas R Borges

    IEEE Transactions on Medical Imaging
    |July 12, 2018
    PubMed
    Summary

    Stabilizing quantum noise in digital mammograms using an adaptive variance stabilizing transform (VST) significantly improves computerized detection of microcalcifications (MCs). This noise reduction enhances lesion identification accuracy in mammography.

    More Related Videos

    Automated Detection and Analysis of Exocytosis
    13:28

    Automated Detection and Analysis of Exocytosis

    Published on: September 11, 2021

    4.0K
    Automated Microbial Cultivation and Adaptive Evolution using Microbial Microdroplet Culture System MMC
    08:18

    Automated Microbial Cultivation and Adaptive Evolution using Microbial Microdroplet Culture System MMC

    Published on: February 18, 2022

    4.6K

    Related Experiment Videos

    Last Updated: Feb 8, 2026

    Calcification of Vascular Smooth Muscle Cells and Imaging of Aortic Calcification and Inflammation
    08:43

    Calcification of Vascular Smooth Muscle Cells and Imaging of Aortic Calcification and Inflammation

    Published on: May 31, 2016

    20.4K
    Automated Detection and Analysis of Exocytosis
    13:28

    Automated Detection and Analysis of Exocytosis

    Published on: September 11, 2021

    4.0K
    Automated Microbial Cultivation and Adaptive Evolution using Microbial Microdroplet Culture System MMC
    08:18

    Automated Microbial Cultivation and Adaptive Evolution using Microbial Microdroplet Culture System MMC

    Published on: February 18, 2022

    4.6K

    Area of Science:

    • Medical Imaging
    • Digital Mammography
    • Image Processing

    Background:

    • Microcalcifications (MCs) are crucial indicators of early breast cancer on mammograms.
    • High-frequency image noise, particularly quantum noise, hinders accurate MC detection.
    • Existing noise models for mammograms often assume a square-root noise dependency.

    Purpose of the Study:

    • To develop and evaluate an adaptive variance stabilizing transform (VST) for digital mammograms.
    • To improve the accuracy of computerized microcalcification detection.
    • To stabilize intensity-dependent quantum noise to a unitary standard deviation.

    Main Methods:

    • Derivation of an adaptive VST based on a square-root noise model.
    • Estimation of noise characteristics directly from individual mammograms.
    • Application of the adaptive VST as a preprocessing step for MC detection algorithms.

    Main Results:

    • Statistically significant improvement in MC detection performance on VST-transformed mammograms across multiple datasets and manufacturers.
    • Adaptive VST outperformed unprocessed mammograms for all tested detection methods.
    • Results were superior to a previously proposed fixed VST.

    Conclusions:

    • Adaptive VST is an effective preprocessing technique for enhancing computerized microcalcification detection in digital mammography.
    • Stabilizing quantum noise variance is critical for improving diagnostic accuracy.
    • The proposed method offers a robust solution for noise reduction in mammographic images.