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 Experiment Videos

[Algorithm for automatic quantification of brain atrophy with computed tomography].

Chuan-fu Li1, Kang-yuan Zhou, Zeng-sheng Chen

  • 1Dept. of Electronic Engineering and Information Science, University of Science and Technology of China.

Zhongguo Yi Liao Qi Xie Za Zhi = Chinese Journal of Medical Instrumentation
|January 20, 2006
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Optimizing the Structure and Electrochemical Properties of Benzoquinone-Embedded COF via Heat Treatment for a High-Energy Organic Cathode.

ACS applied materials & interfaces·2023
Same author

Cardiomyocyte-specific Peli1 contributes to the pressure overload-induced cardiac fibrosis through miR-494-3p-dependent exosomal communication.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology·2022
Same author

Identifying Compound Effect of Drugs on Rheumatoid Arthritis Treatment Based on the Association Rule and a Random Walking-Based Model.

BioMed research international·2020
Same author

Correction to: A20 prevents obesity-induced development of cardiac dysfunction.

Journal of molecular medicine (Berlin, Germany)·2020
Same author

Multiparametric MRI-based radiomics signature for preoperative estimation of tumor-stroma ratio in rectal cancer.

European radiology·2020
Same author

Characterization and ecological function of bacterial communities in seabed sediments of the southwestern Yellow Sea and northwestern East China Sea, Western Pacific.

The Science of the total environment·2020
Same journal

[Study on <i>In Vitro</i> Chromosome Aberration Test for Nanomaterials and Medical Devices Containing Nanomaterials].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation·2026
Same journal

[Research on the Coordinated Mechanism of Medical Device Research and Evaluation in China and the United States].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation·2026
Same journal

[Research and Countermeasure Analysis on the Classification of Brain-Computer Interface Rehabilitation Medical Devices].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation·2026
Same journal

[Development of Portable Sleep Monitoring System].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation·2026
Same journal

[Design and Application of 3D-Printed Individualized Pelvic Prostheses].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation·2026
Same journal

[Study on Standardization Methods of Multi-Source Heterogeneous Data from ICU Medical Devices Based on openEHR].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation·2026
See all related articles

A novel, automated method quantifies brain atrophy using CT scans and medical knowledge. This technique was validated on 2388 subjects, proving effective for diagnosing brain atrophy.

Area of Science:

  • Medical Imaging
  • Neurology
  • Computer Science

Background:

  • Brain atrophy is a key indicator of neurological disorders.
  • Accurate quantification of brain atrophy is crucial for diagnosis and treatment monitoring.
  • Existing methods for brain atrophy quantification can be time-consuming and subjective.

Purpose of the Study:

  • To introduce a novel, fully-automatic method for quantifying brain atrophy.
  • To leverage the unique characteristics of cerebral CT images and prior medical knowledge.
  • To validate the algorithm's performance on a large dataset.

Main Methods:

  • Development of a fully-automatic algorithm for brain atrophy quantification.
  • Utilizing computed tomography (CT) volume data.

Related Experiment Videos

  • Integration of prior medical knowledge specific to cerebral CT imaging.

    • Main Results:

    • The algorithm successfully quantified brain atrophy in a large cohort.
    • Validation performed on 2388 cases, including normal and brain atrophy subjects.
    • Demonstrated the effectiveness and reliability of the automated method.

    Conclusions:

    • The proposed method offers an efficient and accurate approach to brain atrophy quantification.
    • This automated technique has the potential to improve clinical diagnosis and patient management.
    • Further research can explore its application in various neurological conditions.