Sample_of_diagnosed_biopsies_labels.csv
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/1eba0804-6a61-4018-8ef0-3832e414fdc0
description: Sample of labels associated to diagnosed_biopsies. Anatomical pathologists have labeled each slide according to four classes of lesion severity as classified by the World Health Organization: 0: benign (normal or subnormal) 1: low malignant potential (low grade squamous intraepithelial lesion) 2: high malignant potential (high grade squamous intraepithelial lesion) 3: invasive cancer (invasive squamous carcinoma) → It refers to the class of the most severe lesion on the slide (at the slide level, not annotation level).
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/echantillon/diagnosed_biopsies/diagnosed_biopsies_labels.csv
format: csv
issued: 2025-01-21T09:22:17.150000
license: licence-ouverte-open-licence
modified: 2025-01-21T09:26:46.430000

breslow_1_2.zip
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/582e8ee6-4f36-4cac-84eb-b19084d94efd
description: File of images with melanoma between 1 and 2 millimeter
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Visiomel/breslow_1_2.zip
format: zip
issued: 2025-09-16T13:28:44.354000
license: cc-by
modified: 2025-02-28T13:28:09

breslow_empty.zip
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/7585e667-03af-417a-a07b-ddd7e1434351
description: File with melanome with missing value of Breslow
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Visiomel/breslow_empty.zip
format: zip
issued: 2025-09-16T13:27:22.349000
license: cc-by
modified: 2025-02-28T10:04:06

https://dev.data.gouv.fr/api/1/contacts/689b58ac283a66061b0306ce/
type: Kind
fn: Frédéric Staroz
has url: https://www.ouestpathologie.fr/nos-centres/14

Sample_of_diagnosed_conizations_labels.csv
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/47c22574-b945-4689-930f-35f150f4e165
description: Sample of labels associated with diagnosed_conizations. Anatomical pathologists have labeled each slide according to four classes of lesion severity as classified by the World Health Organization: 0: benign (normal or subnormal) 1: low malignant potential (low grade squamous intraepithelial lesion) 2: high malignant potential (high grade squamous intraepithelial lesion) 3: invasive cancer (invasive squamous carcinoma) → It refers to the class of the most severe lesion on the slide (at the slide level, not annotation level).
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/echantillon/diagnosed_conizations/diagnosed_conizations_labels.csv
format: csv
issued: 2025-01-21T09:24:53.721000
license: licence-ouverte-open-licence
modified: 2025-01-21T09:26:24.793000

Sample_of_fully_annotated_biopsies_sample_images.zip
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/62fe7090-881b-4c76-a0fc-ffae862ab373
description: Sample of images of diagnosed_biopsies. Anatomical pathologists have labeled each slide according to four classes of lesion severity as classified by the World Health Organization: 0: benign (normal or subnormal) 1: low malignant potential (low grade squamous intraepithelial lesion) 2: high malignant potential (high grade squamous intraepithelial lesion) 3: invasive cancer (invasive squamous carcinoma) → It refers to the class of the most severe lesion on the slide (at the slide level, not annotation level).
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/echantillon/fully_annotated_biopsies/fully_annotated_biopsies_sample_images.zip
format: tiff
issued: 2025-01-21T09:32:53.383000
license: licence-ouverte-open-licence
modified: 2025-01-21T09:32:53.383000

diagnosed_conizations_metadata.csv
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/850971c9-e128-4496-a96b-7aebb06389e3
description: Metadata associated with diagnosed_conizations (21 slides). Anatomical pathologists have labeled each slide according to four classes of lesion severity as classified by the World Health Organization: 0: benign (normal or subnormal) 1: low malignant potential (low grade squamous intraepithelial lesion) 2: high malignant potential (high grade squamous intraepithelial lesion) 3: invasive cancer (invasive squamous carcinoma) → It refers to the class of the most severe lesion on the slide (at the slide level, not annotation level).
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/diagnosed_conizations/diagnosed_conizations_metadata.csv
format: csv
issued: 2025-01-21T09:14:32.013000
license: licence-ouverte-open-licence
modified: 2024-04-19T12:06:47

Sample_of_diagnosed_biopsies_metadata.csv
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/f0e1dcf0-31d0-4589-80ac-97b6a660a516
description: Sample of metadata associated to diagnosed_biopsies. Anatomical pathologists have labeled each slide according to four classes of lesion severity as classified by the World Health Organization: 0: benign (normal or subnormal) 1: low malignant potential (low grade squamous intraepithelial lesion) 2: high malignant potential (high grade squamous intraepithelial lesion) 3: invasive cancer (invasive squamous carcinoma) → It refers to the class of the most severe lesion on the slide (at the slide level, not annotation level).
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/echantillon/diagnosed_biopsies/diagnosed_biopsies_metadata.csv
format: csv
issued: 2025-01-21T09:23:03.639000
license: licence-ouverte-open-licence
modified: 2025-01-21T09:28:52.952000

breslow_above_or_eq_4.zip
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/0cf4d001-aee1-481a-bd2b-14770553df29
description: File with melanome above 4 mm
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Visiomel/breslow_above_or_eq_4.zip
format: zip
issued: 2025-09-16T13:27:49.326000
license: cc-by
modified: 2025-02-28T13:28:13

diagnosed_conizations_images.zip
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/27384ab0-8b33-4e1e-b49f-d538a9fc6658
description: Images of diagnosed_conizations (21 slides). Anatomical pathologists have labeled each slide according to four classes of lesion severity as classified by the World Health Organization: 0: benign (normal or subnormal) 1: low malignant potential (low grade squamous intraepithelial lesion) 2: high malignant potential (high grade squamous intraepithelial lesion) 3: invasive cancer (invasive squamous carcinoma) → It refers to the class of the most severe lesion on the slide (at the slide level, not annotation level).
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/diagnosed_conizations/diagnosed_conizations_images.zip
format: tiff
issued: 2025-01-21T09:14:52.734000
license: licence-ouverte-open-licence
modified: 2025-01-21T09:14:52.734000

SAMPLE_clinical_variables.csv
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/bceb1763-14af-4fce-a178-e2a0c835b0e6
description: 15 cases of clinical variables
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Visiomel/Sample/clinical_variables_opendata_sample_dataset.csv
format: csv
issued: 2025-09-16T13:25:57.635000
license: cc-by
modified: 2025-03-03T10:47:49

undiagnosed_biopsies_images.zip
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/74499221-22f5-488e-ba4a-3b9449c451e1
description: Images of undiagnosed_biopsies = 217 slides There are no labels for these images or corresponding annotations
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/undiagnosed_biopsies/undiagnosed_biopsies_images.zip
format: tiff
issued: 2025-01-21T09:18:41.066000
license: licence-ouverte-open-licence
modified: 2025-01-21T09:18:41.066000

Sample_of_undiagnosed_biopsies_sample_images.zip
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/388f83b6-38f2-444e-a877-a547d712d45f
description: Sample of images of undiagnosed biopsies. There are no labels for these images or corresponding annotations
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/echantillon/undiagnosed_biopsies/undiagnosed_biopsies_sample_images.zip
format: tiff
issued: 2025-01-21T09:34:58.606000
license: licence-ouverte-open-licence
modified: 2025-01-21T09:36:53.871000

breslow_under_1.zip
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/2ebdfead-27b8-4a8b-9674-66b1fcf84d4a
description: File with melanomes with Breslow under 1 mm
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Visiomel/breslow_under_1.zip
format: zip
issued: 2025-09-16T13:26:58.669000
license: cc-by
modified: 2025-02-28T14:51:20

breslow_2_4.zip
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/612fa537-42f8-4162-ae88-747178954b6f
description: File with melanome images with Breslow between 2 and 4 mm
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Visiomel/breslow_2_4.zip
format: zip
issued: 2025-09-16T13:28:17.420000
license: cc-by
modified: 2025-02-28T13:43:33

SAMPLE images_breslow_.zip
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/1066d637-ba5d-4bf6-ab89-fe92633f7c7e
description: Sample of 15 cases of images.
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Visiomel/Sample/images_breslow_samples.zip
format: zip
issued: 2025-09-16T13:25:04.019000
license: cc-by
modified: 2025-03-03T10:47:00

fully_annotated_biopsies_images.zip
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/8436a162-64c9-4f9b-a3b1-f07028ab4486
description: Images annotated_biopsies (295 slides). Pathologists have labeled and annotated these images to point out regions that represent lesions. When working with the annotations, it's important to keep in mind the following points: - The annotated regions do not necessarily include all lesioned tissue in the slide. An unannotated region is not necessarily normal tissue. - The whole image class label and the annotation class label do not necessarily match. The annotated regions may be the image's labeled class or below. For instance, an image labeled as a class 2 lesion could have annotations representing class 0, 1, or 2. At least some of the annotated regions will represent the most severe/labeled class. All annotations on a slide with label 0 will be normal tissue. - The lesion may fall entirely within the square, or may extend beyond the annotation boundaries. - All annotations are a fixed size of 300x300 micrometers. As images have different resolutions in pixels/micrometer, annotations will have different dimensions in terms of pixels. - When using the geometries, it is important to know the origin of the coordinate system. Image processing software may assume the image origin is either the bottom left or the top left. The WKT shapes that we provide as annotations (geometry column in train_annotations.csv) are relative to the bottom left being the origin (0, 0).
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/fully_annotated_biopsies/fully_annotated_biopsies_images.zip
format: tiff
issued: 2025-01-21T09:17:06.013000
license: licence-ouverte-open-licence
modified: 2025-01-21T09:17:06.013000

TissueNet: detect lesions in uterine cervix specimens - Open data set
type: Dataset
accrual periodicity: AS NEEDED
access rights: PUBLIC
created: 2025-01-14T11:35:56.031000
description: ## **1. Purpose of the database:** This database was collected in order to organize the [TissueNet Data Challenge](https://www.drivendata.org/competitions/67/competition-cervical-biopsy/). This dataset consists of high resolution images of microscopic slides created from cervical biopsies and surgical specimens. Additionally, the competitors were given slide metadata as well as annotations for the training set that outlined some (but not necessarily all) of the lesions present on a slide. The database shared on data.gouv.fr is a portion of the database used for the data challenge. This database contains the slides coming from the pathological centers that have agreed to share the data openly. This database includes 1272 microscopic slides of uterine cervical tissue from medical centers across France. The slides are distributed in the following datasets: diagnosed\_biopsies = 443 slides diagnosed\_conizations = 21 slides annotated\_biopsies = 295 slides undiagnosed\_biopsies = 217 slides undiagnosed\_conizations = 296 slides * **Diagnosed\_biopsies & diagnosed\_conizations:** Pathologists have labeled each slide according to four classes of lesion severity as classified by the World Health Organization (5th edition): 0: benign (normal or subnormal) 1: low malignant potential (low grade squamous intraepithelial lesion) 2: high malignant potential (high grade squamous intraepithelial lesion) 3: invasive cancer (invasive squamous carcinoma) → It refers to the class of the most severe lesion on the slide (at the slide level, not annotation level). * **Fully\_annotated\_biopsies:** Pathologists have labeled and annotated these images to point out regions that represent lesions. When working with the annotations, it's important to keep in mind the following points: \-- The annotated regions do not necessarily include all lesioned tissue in the slide. An unannotated region is not necessarily normal tissue. \-- The whole image class label and the annotation class label do no…
distribution: Sample_of_undiagnosed_conizations_sample_images.zip
distribution: Sample_of_undiagnosed_conizations_metadata.csv
distribution: Sample_of_undiagnosed_biopsies_sample_images.zip
distribution: Sample_of_undiagnosed_biopsies_metadata.csv
distribution: Sample_of_annotations.csv
distribution: Sample_of_fully_annotated_biopsies_sample_images.zip
distribution: Sample_of_annotated_biopsies_metadata.csv
distribution: Sample_of_annotated_biopsies_labels.csv
distribution: Sample_of_diagnosed_conizations_sample_images.zip
distribution: Sample_of_diagnosed_conizations_metadata.csv
distribution: Sample_of_diagnosed_conizations_labels.csv
distribution: Sample_of_diagnosed_biopsies_sample_images.zip
distribution: Sample_of_diagnosed_biopsies_metadata.csv
distribution: Sample_of_diagnosed_biopsies_labels.csv
distribution: undiagnosed_conizations_images.zip
distribution: undiagnosed_conizations_metadata.csv
distribution: undiagnosed_biopsies_images.zip
distribution: undiagnosed_biopsies_metadata.csv
distribution: annotations.csv
distribution: fully_annotated_biopsies_images.zip
distribution: annotated_biopsies_metadata.csv
distribution: annotated_biopsies_labels.csv
distribution: diagnosed_conizations_images.zip
distribution: diagnosed_conizations_metadata.csv
distribution: diagnosed_conizations_labels.csv
distribution: diagnosed_biopsies_images.zip
distribution: diagnosed_biopsies_metadata.csv
distribution: diagnosed_biopsies_labels.csv
issued: 2025-01-14T11:35:56.031000
keyword: artificial-intelligence
keyword: biopsy
keyword: computer-vision
keyword: epithelial-lesions
keyword: french-society-of-pathology
keyword: hdh
keyword: health-data-hub
keyword: ia
keyword: prediction
keyword: sfp
keyword: societe-francaise-de-pathologie
keyword: uterine-cervix
keyword: whole-slide-images
keyword: wsis
landing page: https://dev.data.gouv.fr/datasets/tissuenet-detect-lesions-in-uterine-cervix-specimens-open-data-set
modified: 2025-03-11T09:23:23.152000
publisher: Société Française de Pathologie
alternative label: TissueNet - Open Data
temporal: PeriodOfTime
  end date: 2020-12-31
  start date: 2020-01-01

Sample_of_annotated_biopsies_labels.csv
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/672178b9-e3ad-4de5-b36f-7b9f376f4549
description: Sample of labels associated to diagnosed_biopsies. Anatomical pathologists have labeled each slide according to four classes of lesion severity as classified by the World Health Organization: 0: benign (normal or subnormal) 1: low malignant potential (low grade squamous intraepithelial lesion) 2: high malignant potential (high grade squamous intraepithelial lesion) 3: invasive cancer (invasive squamous carcinoma) → It refers to the class of the most severe lesion on the slide (at the slide level, not annotation level).
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/echantillon/fully_annotated_biopsies/annotated_biopsies_labels.csv
format: csv
issued: 2025-01-21T09:31:34.260000
license: licence-ouverte-open-licence
modified: 2024-04-19T12:07:09

Sample_of_undiagnosed_biopsies_metadata.csv
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/16675b8b-efbd-40a5-bfd5-397a4460e08b
description: Sample of metadata of undiagnosed_biopsies There are no labels for these images or corresponding annotations
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/echantillon/undiagnosed_biopsies/undiagnosed_biopsies_metadata.csv
format: csv
issued: 2025-01-21T09:34:11.574000
license: licence-ouverte-open-licence
modified: 2025-01-21T09:37:14.139000

Société Française de Pathologie
type: Organization

visualized_annotations.pdf
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/d2a9c2c1-c218-4e49-a9a4-be85b0ca2d82
byte size: 94573330
description: This file is a pdf with 16 annotated slides in order to help you understand how pathologists analyse each slides.
download URL: https://static.data.gouv.fr/resources/visiomel-database-predicting-cutaneous-melanoma-relapse/20250929-075507/visualized-annotations.pdf
format: pdf
issued: 2025-09-29T07:55:14.916000
license: cc-by
media type: application/pdf
modified: 2025-09-29T07:55:15.142000

Sample_of_annotated_biopsies_metadata.csv
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/33056dc6-2632-4185-a186-14406a860fec
description: Sample of metadata associated to diagnosed_biopsies. Anatomical pathologists have labeled each slide according to four classes of lesion severity as classified by the World Health Organization: 0: benign (normal or subnormal) 1: low malignant potential (low grade squamous intraepithelial lesion) 2: high malignant potential (high grade squamous intraepithelial lesion) 3: invasive cancer (invasive squamous carcinoma) → It refers to the class of the most severe lesion on the slide (at the slide level, not annotation level).
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/echantillon/fully_annotated_biopsies/annotated_biopsies_metadata.csv
format: csv
issued: 2025-01-21T09:32:11.408000
license: licence-ouverte-open-licence
modified: 2024-04-19T12:07:09

diagnosed_biopsies_labels.csv
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/31b13b93-506f-4f3b-bfed-92e535c8732f
description: Labels associated to diagnosed_biopsies (443 slides). Anatomical pathologists have labeled each slide according to four classes of lesion severity as classified by the World Health Organization: 0: benign (normal or subnormal) 1: low malignant potential (low grade squamous intraepithelial lesion) 2: high malignant potential (high grade squamous intraepithelial lesion) 3: invasive cancer (invasive squamous carcinoma) → It refers to the class of the most severe lesion on the slide (at the slide level, not annotation level).
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/diagnosed_biopsies/diagnosed_biopsies_labels.csv
format: csv
issued: 2025-01-21T09:10:51.287000
license: licence-ouverte-open-licence
modified: 2025-01-21T09:30:05.610000

Sample_of_annotations.csv
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/6055341d-a79e-46e5-aa79-2be298564005
description: Sample of biopsies annotations.
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/echantillon/fully_annotated_biopsies/annotations.csv
format: csv
issued: 2025-01-21T09:33:24.674000
license: licence-ouverte-open-licence
modified: 2024-04-19T12:07:10

undiagnosed_conizations_images.zip
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/a93bdda5-4173-4c02-b1ef-e753b4f18eee
description: Images of undiagnosed conizations (296 slides). There are no labels for these images or corresponding annotations
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/undiagnosed_conizations/undiagnosed_conizations_images.zip
format: tiff
issued: 2025-01-21T09:20:54.427000
license: licence-ouverte-open-licence
modified: 2025-01-21T09:20:54.427000

Sample_of_undiagnosed_conizations_sample_images.zip
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/435bccf9-7ede-46a6-9d1b-838ebbfbafc4
description: Sample of images of undiagnosed conizations. undiagnosed_conizations_sample_images.zip.
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/echantillon/undiagnosed_conizations/undiagnosed_conizations_sample_images.zip
format: tiff
issued: 2025-01-21T09:36:26.450000
license: licence-ouverte-open-licence
modified: 2025-01-21T09:36:48.008000

Société Française de Pathologie
type: Catalog
type: Collection
dataset: VisioMel database: predicting cutaneous melanoma relapse
dataset: TissueNet: detect lesions in uterine cervix specimens - Open data set
description: Société Française de Pathologie
publisher: Société Française de Pathologie
total items: 2
view: https://dev.data.gouv.fr/api/1/organizations/678649260cbf7cb1468b9016/catalog.jsonld

annotations.csv
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/3fb0394b-d71a-4482-b757-54bfc54e2c6b
description: Annotations of biopsies.
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/fully_annotated_biopsies/annotations.csv
format: csv
issued: 2025-01-21T09:17:32.659000
license: licence-ouverte-open-licence
modified: 2024-04-19T12:10:37

diagnosed_conizations_labels.csv
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/ba58ddef-d27e-486f-ac77-85aef518258f
description: Labels associated with diagnosed_conizations (21 slides). Anatomical pathologists have labeled each slide according to four classes of lesion severity as classified by the World Health Organization: 0: benign (normal or subnormal) 1: low malignant potential (low grade squamous intraepithelial lesion) 2: high malignant potential (high grade squamous intraepithelial lesion) 3: invasive cancer (invasive squamous carcinoma) → It refers to the class of the most severe lesion on the slide (at the slide level, not annotation level).
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/diagnosed_conizations/diagnosed_conizations_labels.csv
format: csv
issued: 2025-01-21T09:14:04.790000
license: licence-ouverte-open-licence
modified: 2024-04-19T12:06:47

https://dev.data.gouv.fr/api/1/contacts/689b58c5283a66061b032f5e/
type: Kind
fn: Laurie Alla

diagnosed_biopsies_images.zip
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/138b4d86-4522-457e-8b83-a44a938ffd75
description: Images of diagnosed_biopsies (443 slides). Anatomical pathologists have labeled each slide according to four classes of lesion severity as classified by the World Health Organization: 0: benign (normal or subnormal) 1: low malignant potential (low grade squamous intraepithelial lesion) 2: high malignant potential (high grade squamous intraepithelial lesion) 3: invasive cancer (invasive squamous carcinoma) → It refers to the class of the most severe lesion on the slide (at the slide level, not annotation level).
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/diagnosed_biopsies/diagnosed_biopsies_images.zip
format: tiff
issued: 2025-01-21T09:12:15.241000
license: licence-ouverte-open-licence
modified: 2025-01-21T09:12:15.241000

VisioMel database: predicting cutaneous melanoma relapse
type: Dataset
accrual periodicity: AS NEEDED
contact point: https://dev.data.gouv.fr/api/1/contacts/689b58c5283a66061b032f5e/
access rights: PUBLIC
created: 2025-08-12T15:12:01.536000
description: ## **1. Purpose of the database:** Melanoma is a cancer arising from melanocytes—the pigment-producing cells located primarily in the skin, but also, less commonly, in mucosal membranes. While most cases occur in the skin, mucosal melanomas represent a rarer but clinically significant subset. The pathogenesis of cutaneous melanoma is multifactorial, involving a combination of environmental factors — particularly ultraviolet (UV) radiation — host-related characteristics, such as the presence of atypical nevi, a high total nevus count, and skin phototype, as well as inherited genetic susceptibility. Although they represent only about 10% of all skin cancers, cutaneous melanoma are among the most aggressive forms of skin cancers, primarily due to their high metastatic potential, which critically worsens the prognosis. Metastatic dissemination occurs when malignant cells from the primary tumor invade surrounding tissues and establish secondary lesions in regional lymph nodes (referred to as loco-regional melanoma) or distant organs (distant metastases). Metastases are infrequently present at the time of initial diagnosis and generally emerge during disease monitoring or follow-up. Diagnosis of melanoma involves microscopic analysis of tumor tissue by a pathologist. By examining a stained histological slide, the pathologist confirms the disease diagnosis and assesses lesion severity based on prognostic factors such as the tumor thickness or the presence of ulceration. Combining this analysis with clinical prognostic factors (such as age, sex, and medical history) enables dermatologists to adapt treatment to the disease's severity. Patient survival in melanoma is highly dependent on the stage at diagnosis. In cases of primary cutaneous melanoma without metastatic spread, prognosis is strongly associated with tumor thickness. For example, early-stage melanomas measuring less than 1 mm in thickness have a 5-year survival rate exceeding 95%. In contrast, melanomas thicker th…
distribution: visualized_annotations.pdf
distribution: breslow_1_2.zip
distribution: breslow_2_4.zip
distribution: breslow_above_or_eq_4.zip
distribution: breslow_empty.zip
distribution: breslow_under_1.zip
distribution: clinical_variables_opendata_all_dataset.csv
distribution: SAMPLE_clinical_variables.csv
distribution: SAMPLE images_breslow_.zip
issued: 2025-08-12T15:12:01.536000
keyword: ai
keyword: artificial-intelligence
keyword: cnpath
keyword: computer-vision
keyword: conseil-national-professionnel-des-pathologistes
keyword: cutaneous-cancer-group
keyword: french-society-of-dermatology
keyword: french-society-of-pathplogy
keyword: gcc
keyword: groupe-de-cancerologie-cutanee
keyword: hdh
keyword: health-data-hub
keyword: ia
keyword: melanoma
keyword: national-professional-council-of-pathologists
keyword: prediction
keyword: predictions
keyword: relapse
keyword: sfd
keyword: sfp
keyword: societe-francaise-de-dermatologie
keyword: societe-francaise-de-pathologie
keyword: visiomel
keyword: whole-slide-imaging
keyword: wsis
landing page: https://dev.data.gouv.fr/datasets/visiomel-database-predicting-cutaneous-melanoma-relapse
modified: 2025-09-29T07:55:15.145000
publisher: Société Française de Pathologie
temporal: PeriodOfTime
  end date: 2016-12-30
  start date: 2012-01-01

clinical_variables_opendata_all_dataset.csv
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/256f94d0-9b58-4ee9-a26a-e50753c2d84c
description: File with clinical variables associated with (all Breslow)
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Visiomel/clinical_variables_opendata_all_dataset.csv
format: csv
issued: 2025-09-16T13:26:31.361000
license: cc-by
modified: 2025-03-03T10:41:10

Sample_of_diagnosed_conizations_metadata.csv
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/3760b8eb-1734-4455-b96d-1eb56d6613fc
description: Sample of metadata associated with diagnosed_conizations. Anatomical pathologists have labeled each slide according to four classes of lesion severity as classified by the World Health Organization: 0: benign (normal or subnormal) 1: low malignant potential (low grade squamous intraepithelial lesion) 2: high malignant potential (high grade squamous intraepithelial lesion) 3: invasive cancer (invasive squamous carcinoma) → It refers to the class of the most severe lesion on the slide (at the slide level, not annotation level).
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/echantillon/diagnosed_conizations/diagnosed_conizations_metadata.csv
format: csv
issued: 2025-01-21T09:26:14.809000
license: licence-ouverte-open-licence
modified: 2025-01-21T09:29:00.024000

undiagnosed_biopsies_metadata.csv
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/37b7de0f-eb66-4b9f-b3eb-cb8c13942c1b
description: Metadata of undiagnosed_biopsies = 217 slides There are no labels for these images or corresponding annotations
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/undiagnosed_biopsies/undiagnosed_biopsies_metadata.csv
format: csv
issued: 2025-01-21T09:18:15.717000
license: licence-ouverte-open-licence
modified: 2024-04-19T12:16:44

Sample_of_diagnosed_biopsies_sample_images.zip
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/2454872a-24c1-4fa7-940d-a1c93a0c9799
description: Sample of images of diagnosed_biopsies. Anatomical pathologists have labeled each slide according to four classes of lesion severity as classified by the World Health Organization: 0: benign (normal or subnormal) 1: low malignant potential (low grade squamous intraepithelial lesion) 2: high malignant potential (high grade squamous intraepithelial lesion) 3: invasive cancer (invasive squamous carcinoma) → It refers to the class of the most severe lesion on the slide (at the slide level, not annotation level).
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/echantillon/diagnosed_biopsies/diagnosed_biopsies_sample_images.zip
format: tiff
issued: 2025-01-21T09:23:44.690000
license: licence-ouverte-open-licence
modified: 2025-01-21T09:26:33.145000

Sample_of_undiagnosed_conizations_metadata.csv
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/f1404663-a4e2-4e0b-b051-3edda58ea94e
description: Sameple of metadata associated with undiagnosed conizations. There are no labels for these images or corresponding annotations
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/echantillon/undiagnosed_conizations/undiagnosed_conizations_metadata.csv
format: csv
issued: 2025-01-21T09:35:44.821000
license: licence-ouverte-open-licence
modified: 2024-04-19T12:10:36

Sample_of_diagnosed_conizations_sample_images.zip
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/5c15dea3-833d-4760-a0ec-9252dd21271f
description: Sample of images of diagnosed_conizations. Anatomical pathologists have labeled each slide according to four classes of lesion severity as classified by the World Health Organization: 0: benign (normal or subnormal) 1: low malignant potential (low grade squamous intraepithelial lesion) 2: high malignant potential (high grade squamous intraepithelial lesion) 3: invasive cancer (invasive squamous carcinoma) → It refers to the class of the most severe lesion on the slide (at the slide level, not annotation level).
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/echantillon/diagnosed_conizations/diagnosed_conizations_sample_images.zip
format: tiff
issued: 2025-01-21T09:28:45.029000
license: licence-ouverte-open-licence
modified: 2025-01-21T09:28:45.029000

diagnosed_biopsies_metadata.csv
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/06f4c44d-b0ea-4a19-9449-8fd0a193503d
description: Metadata associated to diagnosed_biopsies (443 slides). Anatomical pathologists have labeled each slide according to four classes of lesion severity as classified by the World Health Organization: 0: benign (normal or subnormal) 1: low malignant potential (low grade squamous intraepithelial lesion) 2: high malignant potential (high grade squamous intraepithelial lesion) 3: invasive cancer (invasive squamous carcinoma) → It refers to the class of the most severe lesion on the slide (at the slide level, not annotation level).
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/diagnosed_biopsies/diagnosed_biopsies_metadata.csv
format: csv
issued: 2025-01-21T09:11:24.349000
license: licence-ouverte-open-licence
modified: 2024-04-23T07:43:45

annotated_biopsies_labels.csv
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/bcbefd04-b99d-4e5f-84b4-fc580f493495
description: Labels associted to annotated_biopsies (295 slides). Pathologists have labeled and annotated these images to point out regions that represent lesions. When working with the annotations, it's important to keep in mind the following points: - The annotated regions do not necessarily include all lesioned tissue in the slide. An unannotated region is not necessarily normal tissue. - The whole image class label and the annotation class label do not necessarily match. The annotated regions may be the image's labeled class or below. For instance, an image labeled as a class 2 lesion could have annotations representing class 0, 1, or 2. At least some of the annotated regions will represent the most severe/labeled class. All annotations on a slide with label 0 will be normal tissue. - The lesion may fall entirely within the square, or may extend beyond the annotation boundaries. - All annotations are a fixed size of 300x300 micrometers. As images have different resolutions in pixels/micrometer, annotations will have different dimensions in terms of pixels. - When using the geometries, it is important to know the origin of the coordinate system. Image processing software may assume the image origin is either the bottom left or the top left. The WKT shapes that we provide as annotations (geometry column in train_annotations.csv) are relative to the bottom left being the origin (0, 0).
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/fully_annotated_biopsies/annotated_biopsies_labels.csv
format: csv
issued: 2025-01-21T09:16:16.199000
license: licence-ouverte-open-licence
modified: 2024-04-19T12:10:36

undiagnosed_conizations_metadata.csv
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/0e4a5008-8687-4e25-abb4-0d6d03d5dc41
description: Metadata of undiagnosed conizations (296 slides). There are no labels for these images or corresponding annotations
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/undiagnosed_conizations/undiagnosed_conizations_metadata.csv
format: csv
issued: 2025-01-21T09:20:33.680000
license: licence-ouverte-open-licence
modified: 2024-04-19T12:56:16

annotated_biopsies_metadata.csv
type: Distribution
access URL: https://dev.data.gouv.fr/api/1/datasets/r/e77e30d7-d652-43d6-b7f8-df6d63f9fbf2
description: Metadata associted to annotated_biopsies (295 slides). Pathologists have labeled and annotated these images to point out regions that represent lesions. When working with the annotations, it's important to keep in mind the following points: - The annotated regions do not necessarily include all lesioned tissue in the slide. An unannotated region is not necessarily normal tissue. - The whole image class label and the annotation class label do not necessarily match. The annotated regions may be the image's labeled class or below. For instance, an image labeled as a class 2 lesion could have annotations representing class 0, 1, or 2. At least some of the annotated regions will represent the most severe/labeled class. All annotations on a slide with label 0 will be normal tissue. - The lesion may fall entirely within the square, or may extend beyond the annotation boundaries. - All annotations are a fixed size of 300x300 micrometers. As images have different resolutions in pixels/micrometer, annotations will have different dimensions in terms of pixels. - When using the geometries, it is important to know the origin of the coordinate system. Image processing software may assume the image origin is either the bottom left or the top left. The WKT shapes that we provide as annotations (geometry column in train_annotations.csv) are relative to the bottom left being the origin (0, 0).
download URL: https://oos.eu-west-2.outscale.com/hdh-datachallenge/Tissuenet/fully_annotated_biopsies/annotated_biopsies_metadata.csv
format: csv
issued: 2025-01-21T09:16:39.145000
license: licence-ouverte-open-licence
modified: 2024-04-19T12:10:36