Holoscan Sample App Data for AI Colonoscopy Segmentation of Polyps

This resource contains a segmentation model for the identification of polyps during colonoscopies trained on the Kvasir-SEG dataset [1], using the ColonSegNet model architecture [2], as well as a sample surgical video.

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[1] Jha, Debesh, Pia H. Smedsrud, Michael A. Riegler, Pål Halvorsen, Thomas de Lange, Dag Johansen, and Håvard D. Johansen, \"Kvasir-seg: A segmented polyp dataset\" Proceedings of the International Conference on Multimedia Modeling, pp. 451-462, 2020.
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[2] Jha D, Ali S, Tomar NK, Johansen HD, Johansen D, Rittscher J, Riegler MA, Halvorsen P. Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning. IEEE Access. 2021 Mar 4;9:40496-40510. doi: 10.1109/ACCESS.2021.3063716. PMID: 33747684; PMCID: PMC7968127.
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Model

Given an RGB image of 512 x 512, this model provides semantic segmentation of the polyps. Each pixel stores a confidence score of [0,1] for polyp presence.

Note: The provided model is in ONNX format. It will automatically be converted into a TensorRT model (.engine) the first time it is processed by a Holoscan application.

Inputs

INPUT__0 - Input RGB image (batchsize, height, width, channels)\n
- shape=[1, 512, 512, 3]
- dtype=float32
- range=[0, 255]
\n

Outputs

output_old - Segmentation output with per-pixel confidence [0,1].\n
- shape=[1, 512, 512]
- dtype=float32
- range=[0, 1]
\n

Video Data

The sample data, provided by Simula Research Laboratory, is an .mp4 video of a colonoscopy scene with a polyp identified by the model.

Note: the .mp4 file must be converted into a GXF tensor file using the convert_video_to_gxf_entities.py script on GitHub to be used with the VideoStreamReplayer Holoscan operator.

License

Refer to the license agreement for use of the sample data.

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Smedsrud, Michael A. Riegler, Pål Halvorsen, Thomas de Lange, Dag Johansen, and Håvard D. Johansen, \"Kvasir-seg: A segmented polyp dataset\" Proceedings of the *International Conference on Multimedia Modeling*, pp. 451-462, 2020.\n\n> [2] Jha D, Ali S, Tomar NK, Johansen HD, Johansen D, Rittscher J, Riegler MA, Halvorsen P. Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning. *IEEE Access*. 2021 Mar 4;9:40496-40510. doi: 10.1109/ACCESS.2021.3063716. PMID: 33747684; PMCID: PMC7968127.\n\n## Model\n\nGiven an RGB image of `512 x 512`, this model provides semantic segmentation of the polyps. Each pixel stores a confidence score of [0,1] for polyp presence.\n\n_Note: The provided model is in ONNX format. It will automatically be converted into a TensorRT model (.engine) the first time it is processed by a Holoscan application._\n\n### Inputs\n\n- `INPUT__0` - Input RGB image (batchsize, height, width, channels)\n - `shape=[1, 512, 512, 3]`\n - `dtype=float32`\n - `range=[0, 255]`\n\n### Outputs\n\n- `output_old` - Segmentation output with per-pixel confidence [0,1].\n - `shape=[1, 512, 512]`\n - `dtype=float32`\n - `range=[0, 1]`\n\n## Video Data\n\nThe sample data, provided by [Simula Research Laboratory](https://www.simula.no/), is an .mp4 video of a colonoscopy scene with a polyp identified by the model.\n\n_Note: the .mp4 file must be converted into a GXF tensor file using the `convert_video_to_gxf_entities.py` script on [GitHub](https://github.com/nvidia-holoscan/holoscan-sdk/tree/main/scripts#convert_video_to_gxf_entitiespy) to be used with the `VideoStreamReplayer` Holoscan operator._\n\n## License\n\nRefer to the [license agreement](https://developer.nvidia.com/clara-holoscan-EULA) for use of the sample data.","displayName","Colonoscopy Sample App Data",["D",1681919489745],"publisher","NVIDIA","latestVersion","versions","collectionCounts","imageUrl","/api/image/nvidia/clara-holoscan/resources/holoscan_colonoscopy_sample_data","rawImageUrl","https://avatars.githubusercontent.com/u/119712212","canGuestDownload","latestVersionSizeInBytes",22956185,"licenseTerms","isMultinodeEnabled","isMultiArchitecture","bias","explainability","privacy","safetyAndSecurity","featureLabels",[],"displayLabels",[302,303,304,305,306,307],"policyLabels",[],"systemLabels",[],"products",[],"hasNimMetadata",{"_269":331,"_309":332,"_311":333,"_313":314},{"_269":328,"_309":329,"_311":330,"_313":314},{"_269":325,"_309":326,"_311":327,"_313":314},{"_269":321,"_309":322,"_311":323,"_313":314},{"_269":317,"_309":318,"_311":319,"_313":314},{"_269":308,"_309":310,"_311":312,"_313":314},"ML","value","soln_ml","filter",{"_315":316,"_309":310},"category","label","field","technology","Holoscan","pltfm_clara_holoscan",{"_315":320,"_309":318},"platform","Healthcare","indus_healthcare",{"_315":324,"_309":322},"industry","DL","soln_dl",{"_315":316,"_309":326},"Clara","pltfm_clara",{"_315":320,"_309":329},"AI","soln_ai",{"_315":316,"_309":332},{"_167":1509,"_169":1510},"ngcApps",[1462],"csaApiBaseUrl","https://www.nvidia.com/ai-agents/csa-agent/dcsm","datadogRum",{"_1444":1445,"_1446":1447,"_1448":1449,"_1450":1451,"_1452":345,"_194":369,"_1453":1454,"_1442":56,"_1455":146,"_1456":146,"_1457":1458,"_1459":146,"_1460":1461},"amplitude",{"_1440":1441,"_1442":56,"_1042":-7,"_1443":31},"disableJs","environment","prod","featureFlagsBlob","JTdCJTIydGVzdEZsYWclMjIlM0FmYWxzZSUyQyUyMnNob3dTZWFyY2hMYWJlbFNldEZpbHRlcnMlMjIlM0FmYWxzZSUyQyUyMmNoaW5hTmltRGlzdHJpYnV0b3JzUmVkZXNpZ24lMjIlM0F0cnVlJTJDJTIyZW5hYmxlQ3NhV2lkZ2V0JTIyJTNBZmFsc2UlMkMlMjJlbmFibGVQcm9kdWN0R3JvdXBpbmdCeVN1YnNjcmlwdGlvbiUyMiUzQWZhbHNlJTJDJTIyY29udGFpbmVyU2Nhbm5pbmdSZWRlc2lnbk0xJTIyJTNBZmFsc2UlN0Q=","featureFlagsGuarded","isDevLikeEnv","isPlaywright","isMobileDevice","categorizedOrgs",{"_1434":1435,"_1436":1437,"_1438":1439},"currentOrgContext","currentContextRoles",[],"enterpriseOrgs",[],"locale","en","ngcApiOrigin","ngcHelmOrigin","origin","https://catalog.ngc.nvidia.com","usesMocks","theme","year",2026,"1.4.0","defaultSearchSuggestions",{"_1317":238,"_1318":1319,"_1320":1321,"_1322":1323},"announcements",[],"consentState",{"_408":1307,"_1308":146,"_1309":31,"_1310":31,"_1311":1312},"consentConfig",{"_390":391,"_392":393,"_394":395,"_396":397,"_398":399,"_400":401,"_402":403,"_404":405,"_406":407,"_408":409},"showContactAdmin",1782934096884,[],[],[383,384,385,386,387,388],{"_45":59,"_47":70,"_49":162,"_51":-5,"_53":-5,"_55":56},{"_45":59,"_47":68,"_49":162,"_51":-5,"_53":-5,"_55":56},{"_45":59,"_47":66,"_49":162,"_51":-5,"_53":-5,"_55":56},{"_45":59,"_47":60,"_49":162,"_51":-5,"_53":-5,"_55":56},{"_45":57,"_47":58,"_49":162,"_51":-5,"_53":-5,"_55":56},{"_45":46,"_47":48,"_49":50,"_51":52,"_53":389,"_55":56},4,"mainInfoText","We and our third-party partners (including social media, advertising, and analytics partners) use cookies and other tracking technologies to collect, store, monitor, and process certain information about you when you visit our website. 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Name	Size	Updated	Actions


NVIDIA Colonoscopy Software License (9Sept2022).docx	41.6 KB	November 29, 2022 UTC	curl wget Download
NVIDIA-Clara-Holoscan-SDK-EULA.pdf	155.83 KB	November 29, 2022 UTC	curl wget Download