NCT04551235

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

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 900 (estimated)
• Sponsor: National Taiwan University Hospital · Academic / Other
• Sex: All
• Age: 20 Years
• Healthy volunteers: Not accepted

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.

Conditions

• Hematologic Diseases
• Artificial Intelligence
• Acute Leukemia

Interventions

Type	Name	Description
OTHER	there are not any interventions in this study	there are not any interventions in this study

Timeline

• Start date: 2020-08-28
• Primary completion: 2023-12-31
• Completion: 2023-12-31
• First posted: 2020-09-16
• Last updated: 2022-03-10

Locations

1 site across 1 country: Taiwan