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

National Taiwan University

Status: Unknown

Conditions: Acute Leukemia; Artificial Intelligence; Hematologic Diseases

Treatments: Other: there are not any interventions in this study

Study type: Observational

Funder types: Other

Identifiers

NCT04551235

202007086RIPB

Details and patient eligibility

About

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.

Enrollment: 900 estimated patients

Sex: All

Ages: 20+ years old

Volunteers: No Healthy Volunteers

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