Papillomavirus as the cause of diseases classified to other chapters - Female, 33 - Tissue image [9160729581059951] - Open Research Data - Bridge of Knowledge

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Papillomavirus as the cause of diseases classified to other chapters - Female, 33 - Tissue image [9160729581059951]

Description

This is the histopathological image of CERVIX UTERI tissue 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: 33

Clinical description: Histerectomy with bilateral fallopian tubes due to HSIL dysplasia confirmed by histopathological examination (colposcopy biopsy)

Gender: Female

Diagnosis:

Classification: ICD-10_10-20

Classification code: Chapter I - Certain infectious and parasitic diseases

Diagnosis: Papillomavirus as the cause of diseases classified to other chapters

Result of the histopathological examination: A fragment of the exocervix covered with a paraepidermal epithelium with koilocytosis.

Sample:

Material: FFPE

Collecting method: Surgical specimen

Topography: FEMALE GENITAL ORGANS

Organ: CERVIX UTERI

Tissue: Exocervix

Type of staining: positive/HE

Staining: Not applicable

Antibody: Not applicable

Technology:

Equipment: Pannoramic 250 3DHistech

Lens: 20x

Organization:

Source: Medical University Gdańsk

Dataset file

1ea724e3-ea51-41b4-aab3-947fa45a13ea
3.8 GB, S3 ETag , downloads: 23
The file hash is calculated from the formula
hexmd5(md5(part1)+md5(part2)+...)-{parts_count} where a single part of the file is 512 MB in size.

Example script for calculation:
https://github.com/antespi/s3md5

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:
2020-09-26
Creation date:
2020
Dataset language:
English
Fields of science:
  • medical sciences (Medical and Health Sciences )
DOI:
DOI ID 10.34808/04vx-rn45 open in new tab
Ethical papers:
NKBBN/421-306/2020
Verified by:
Medical University of Gdańsk

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