Inflammatory disease of cervix uteri - Female, 49 - Tissue image [6090730014735201] - Open Research Data - Bridge of Knowledge

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Inflammatory disease of cervix uteri - Female, 49 - Tissue image [6090730014735201]

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: 49

Clinical description: Condition after left adnexectomy and right salpingectomy. Endometrioid borderline tumor of the left ovary.

Gender: Female

Diagnosis:

Classification: ICD-10_10-20

Classification code: Chapter XIV - Diseases of the genitourinary system

Diagnosis: Inflammatory disease of cervix uteri

Result of the histopathological examination: Endocervix segmentally in the state of chronic active inflammation with a low degree of severity of lesions with areas of squamous metaplasia, with the presence of a few small retention mucous cysts in the stroma.

Sample:

Material: FFPE

Collecting method: Surgical specimen

Topography: FEMALE GENITAL ORGANS

Organ: CERVIX UTERI

Tissue: Cervical canal

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

38210901-3be4-43d4-a49b-6e0454e83826
9.4 GB, S3 ETag , downloads: 2
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:
2022
Verification date:
2022-06-06
Creation date:
2022
Dataset language:
English
Fields of science:
  • medical sciences (Medical and Health Sciences )
DOI:
DOI ID 10.34808/mpp0-d926 open in new tab
Ethical papers:
NKBBN/421-306/2020
Verified by:
Medical University of Gdańsk

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