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Clinical Trials/NCT04551235
NCT04551235UnknownNot Applicable

Establishing Automatic Method of Counting and Classify Bone Marrow and Peripheral Blood Cells

National Taiwan University Hospital1 site in 1 country900 target enrollmentStarted: August 28, 2020Last updated:
Conditions

Trial Snapshot

Phase
Not Applicable
Enrollment
900
Locations
1
Primary Endpoint
Evaluate the accuracy of cell counting and classifying between automatic method and manual method through digital microscopic photos of bone marrow smear and peripheral blood smear using deep convolutional neural networks

Study Overview

Brief Summary

Counting and classification of blood cells in a bone marrow smear and peripheral blood smear are essential to clinical hematology. To this date, this procedure has been carried out in a manual manner in the great majority of clinical settings. There is often inconsistency in the counting result between different operators largely due to its manual nature. There has not been an effective and standard method for blood smear preparation and automatic counting and classification. The recent advent of deep neural network for medical image processing introduced new opportunities for an effective solution of this long-standing problem. Numerous results have been published on the effectiveness of convolutional neural network in clinical image recognition task.

Study Design

Study Type
Observational
Observational Model
Case Only
Time Perspective
Prospective

Eligibility Criteria

Ages
20 Years to — (Adult, Older Adult)
Sex
All
Accepts Healthy Volunteers
No

Inclusion Criteria

  • •Patients who have suspected or confirmed hematological diseases and receive bone
  • •marrow or peripheral blood cell morphological examination in National Taiwan University Cancer Center
  • •Patients who are aged more than 20 y/o

Exclusion Criteria

  • •Patients who are not willing to sign informed consents

Outcomes

Primary Outcomes

Evaluate the accuracy of cell counting and classifying between automatic method and manual method through digital microscopic photos of bone marrow smear and peripheral blood smear using deep convolutional neural networks

Time Frame: 3 years

Secondary Outcomes

No secondary outcomes reported

Investigators

Sponsor Class
Other
Responsible Party
Sponsor

Study Sites (1)

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