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

Transformation01:26

Transformation

502
Microbial communities are dynamic environments where cell lysis releases free DNA into the surroundings. Other cells can take up this extracellular DNA through a process known as transformation.When a cell incorporates this foreign DNA into its genome, resulting in genetic modification, the process is known as transformation. Cells capable of this process are termed competent. Competence can be natural, as observed in certain bacteria and archaea, or artificially induced in the...
502
Transformations of Functions III01:20

Transformations of Functions III

78
Transformations modify the graphical representation of a function without changing its fundamental form. One common transformation is reflection, which flips the graph across a designated axis. When the vertical coordinates of all points are multiplied by the negative one, the entire graph is mirrored over the horizontal axis. This transformation reverses the vertical orientation of peaks and troughs, akin to signal inversion in electrical systems, where a waveform is flipped, but the timing of...
78
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

172
DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
172
Computed Tomography01:10

Computed Tomography

7.7K
Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
7.7K
Transformations of Functions II01:29

Transformations of Functions II

70
Transformations in mathematics alter the position or orientation of a function’s graph while preserving its fundamental shape. One important type of transformation is the horizontal shift, which involves modifying the input variable within a function’s equation. This operation affects where outputs occur along the horizontal axis but does not alter the function’s overall structure.A horizontal shift is achieved by replacing the input variable x with either x + c or x - c,...
70
Properties of the z-Transform I01:17

Properties of the z-Transform I

507
The z-transform is a fundamental tool in digital signal processing, enabling the analysis of discrete-time systems through its various properties. It is an invaluable tool for analyzing discrete-time systems, offering a range of properties that simplify complex signal manipulations. One fundamental property is linearity. For any two discrete-time signals, the z-transform of their linear combination equals the same linear combination of their individual z-transforms. This property is essential...
507

You might also read

Related Articles

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

Sort by
Same author

GUSL: A novel and efficient machine learning model for prostate segmentation on MRI.

Computers in biology and medicine·2026
Same author

CROSS-MODAL FINE-TUNING OF 3D CONVOLUTIONAL FOUNDATION MODELS FOR ADHD CLASSIFICATION WITH LOW-RANK ADAPTATION.

Proceedings. IEEE International Symposium on Biomedical Imaging·2026
Same author

A transparent, lightweight and sustainable Green Learning AI model for prostate cancer detection on MRI.

BJU international·2026
Same author

A Study on Energy Consumption in AI-Driven Medical Image Segmentation.

Journal of imaging·2025
Same author

Prediction of PD-L1 and CD68 in Clear Cell Renal Cell Carcinoma with Green Learning.

Journal of imaging·2025
Same author

Re: Baris Turkbey, Henkjan Huisman, Andriy Fedorov, et al. Requirements for AI Development and Reporting for MRI Prostate Cancer Detection in Biopsy-Naïve Men: PI-RADS Steering Committee, Version 1.0. Radiology 2025;315:e24014.

European urology·2025

Related Experiment Video

Updated: Dec 8, 2025

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
07:13

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

1.6K

Image Coding with Data-Driven Transforms: Methodology, Performance and Potential.

Xinfeng Zhang, Chao Yang, Xiaoguang Li

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |September 24, 2020
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces an efficient Karhunen-Loéve transform (KLT) image compression algorithm. The novel method optimizes transform sizes and uses band-adaptive quantization for superior performance over existing standards.

    More Related Videos

    Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
    13:44

    Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

    Published on: August 30, 2013

    43.4K
    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
    11:34

    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

    Published on: December 3, 2013

    15.9K

    Related Experiment Videos

    Last Updated: Dec 8, 2025

    Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
    07:13

    Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

    Published on: October 27, 2023

    1.6K
    Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
    13:44

    Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

    Published on: August 30, 2013

    43.4K
    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
    11:34

    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

    Published on: December 3, 2013

    15.9K

    Area of Science:

    • Digital image processing
    • Data compression algorithms
    • Signal processing

    Background:

    • Image compression is crucial due to the exponential growth of digital images.
    • Current methods rely on transforms to reduce spatial correlation by moving data to the frequency domain.
    • The Karhunen-Loéve transform (KLT) offers a data-driven approach by deriving kernels from specific image data using Principal Component Analysis (PCA).

    Purpose of the Study:

    • To develop a highly efficient KLT-based image compression algorithm.
    • To investigate the impact of variable transform sizes and adaptive category selection on compression performance.
    • To propose a band-adaptive quantization scheme based on transform coefficient analysis.

    Main Methods:

    • Utilizing Principal Component Analysis (PCA) to derive Karhunen-Loéve transform (KLT) kernels.
    • Implementing adaptive selection of multiple transform sizes and categories based on rate-distortion (RD) costs.
    • Analyzing transform coefficients to develop a band-adaptive quantization strategy.

    Main Results:

    • The proposed KLT-based algorithm demonstrates significant coding gains.
    • Performance improvements are observed across class-specific and general image datasets.
    • The method outperforms established standards like JPEG and JPEG 2000, as well as dictionary learning approaches.

    Conclusions:

    • The adaptive KLT image compression algorithm offers superior efficiency and performance.
    • Variable transform sizes and band-adaptive quantization are key to achieving high compression ratios.
    • This data-driven approach represents a significant advancement in image compression technology.