An Open Dataset of Annotated Metaphase Cell Images for Chromosome Identification.
Sci Data
; 10(1): 104, 2023 02 23.
Article
en En
| MEDLINE
| ID: mdl-36823215
ABSTRACT
Chromosomes are a principal target of clinical cytogenetic studies. While chromosomal analysis is an integral part of prenatal care, the conventional manual identification of chromosomes in images is time-consuming and costly. This study developed a chromosome detector that uses deep learning and that achieved an accuracy of 98.88% in chromosomal identification. Specifically, we compiled and made available a large and publicly accessible database containing chromosome images and annotations for training chromosome detectors. The database contains five thousand 24 chromosome class annotations and 2,000 single chromosome annotations. This database also contains examples of chromosome variations. Our database provides a reference for researchers in this field and may help expedite the development of clinical applications.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Cromosomas
Tipo de estudio:
Diagnostic_studies
/
Guideline
Límite:
Female
/
Humans
/
Pregnancy
Idioma:
En
Revista:
Sci Data
Año:
2023
Tipo del documento:
Article
País de afiliación:
Taiwán