Abnormal cytological findings - Female, 31 - Cell image [71407295768431] - Open Research Data - Bridge of Knowledge

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Abnormal cytological findings - Female, 31 - Cell image [71407295768431]

Description

This is the histopathological image of CERVIX UTERI cell sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.

The detailed information about the patient, sample, and diagnosis are as follows:

Patient:

Age: 31

Clinical description: Prophylaxis. Erosion.

Gender: Female

Diagnosis:

Classification: ICD-10_10-20

Classification code: Chapter XVIII - Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified

Diagnosis: Abnormal cytological findings

Result of the histopathological examination: ASC-US (Atypical squamous cells of undetermined significance). Papsmear contains multiple superficial epithelial cells, partly with inadequate N/C ratio, part of the nuclei are hyperchromatic and/ or have irregular contour (not enough to definitely diagnose koilocytosis), groups of glandular cervical cells. Among them granulocytes can be spotted.

Sample:

Material: SurePath

Collecting method: Exfoliative cytology

Topography: FEMALE GENITAL ORGANS

Organ: CERVIX UTERI

Tissue: Exocervix

Type of staining: positive/HC

Staining: Papanicolaou

Antibody: Not applicable

Technology:

Equipment: Pannoramic 250 3DHistech

Lens: 20x

Organization:

Source: Medical University Gdańsk

Dataset file

a051bedc-ae55-4009-ac26-70a5e3eb58dc
20.2 GB, S3 ETag , downloads: 2
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hexmd5(md5(part1)+md5(part2)+...)-{parts_count} where a single part of the file is 512 MB in size.

Example script for calculation:
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File details

License:
Creative Commons: by-nc-sa 4.0 open in new tab
CC BY-NC-SA
Non-commercial - Share-alike
Raw data:
Data contained in dataset was not processed.
Software:
CaseViewer 2.3

Details

Year of publication:
2021
Verification date:
2021-03-09
Creation date:
2021
Dataset language:
English
Fields of science:
  • medical sciences (Medical and Health Sciences )
DOI:
DOI ID 10.34808/22h5-z019 open in new tab
Ethical papers:
NKBBN/421-306/2020
Verified by:
Medical University of Gdańsk

Keywords

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