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Using Deep Learning Methods to Analyze Automated Breast Ultrasound and Hand-held Ultrasound Images, to Establish a Diagnosis, Therapy Assessment and Prognosis Prediction Model of Breast Cancer.

NCT04270032 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 10000

Last updated 2022-01-27

No results posted yet for this study

Summary

The purpose of this study is using a deep learning method to analyze the automated breast ultrasound (ABUS) and hand-held ultrasound(HHUS) images, establish and evaluate a diagnosis, therapy assessment and prognosis prediction model of breast cancer. The model would provide important references for further early prevention, early diagnosis and personalized treatment.

Conditions

Interventions

DIAGNOSTIC_TEST

ABUS and HHUS

Using deep learning method to analyze and extract the features of automated breast ultrasound and hand-held ultrasound images

Sponsors & Collaborators

  • Seoul National University Bundang Hospital

    collaborator OTHER

  • Xidian University

    collaborator OTHER

  • Shenzhen University

    collaborator OTHER

  • The First Affiliated Hospital of the Fourth Military Medical University

    lead OTHER

Principal Investigators

  • Hongping Song, MD · Xijing hospital of The fourth military medical university

Eligibility

Min Age
18 Years
Sex
FEMALE
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2020-02-01
Primary Completion
2024-09-01
Completion
2024-09-01
FDA Device
Yes

Countries

  • China

Study Locations

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Entities

Diseases
Companies

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04270032 on ClinicalTrials.gov