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Model Review

3D-UNet allows for seamless segmentation of 3D volumes, with high accuracy and\nperformance, and can be adapted to solve many different segmentation problems.\nIn this resource we use a 3D-UNet model for brain tumor segmentation.

3D-UNet consists of a contractive and expanding path. It repeatedly applies\nunpadded convolutions followed by max pooling for downsampling. Every step in the\nexpanding path consists of an upsampling of the feature maps and a concatenation\nwith the correspondingly cropped feature map from the contractive path.

Requirements

This repository contains Dockerfile which extends the TensorFlow NGC container and encapsulates some dependencies.

Aside from these dependencies, ensure you have the following components:

NVIDIA Docker
TensorFlow 20.06-tf1-py3 NGC container
GPU-based architecture:\n
- NVIDIA Volta
- NVIDIA Turing
- NVIDIA Ampere architecture
\n

To train your model using mixed or TF32 precision with Tensor Cores or using FP32,\nfollow the quick start guide steps and run the model using the default parameters\nof the 3D-UNet model on the Brain Tumor Segmentation 2019 dataset.

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It repeatedly applies\nunpadded convolutions followed by max pooling for downsampling. Every step in the\nexpanding path consists of an upsampling of the feature maps and a concatenation\nwith the correspondingly cropped feature map from the contractive path.\n\n## Requirements\nThis repository contains Dockerfile which extends the TensorFlow NGC container and encapsulates some dependencies. \n\nAside from these dependencies, ensure you have the following components:\n\n- NVIDIA Docker\n- TensorFlow 20.06-tf1-py3 NGC container\n- GPU-based architecture:\n - NVIDIA Volta\n - NVIDIA Turing\n - NVIDIA Ampere architecture\n\n\nTo train your model using mixed or TF32 precision with Tensor Cores or using FP32,\nfollow the quick start guide steps and run the model using the default parameters\nof the 3D-UNet model on the Brain Tumor Segmentation 2019 dataset.","displayName","Notebook for Medical Image Segmentation",["D",1680632812649],"publisher","NVIDIA","latestVersion","versions","collectionCounts","imageUrl","/api/image/nvidia/-/resources/med_3dunet","rawImageUrl","https://assets.nvidiagrid.net/ngc/logos/Tutorials.png","canGuestDownload","latestVersionSizeInBytes","licenseTerms","isMultinodeEnabled","isMultiArchitecture","bias","explainability","privacy","safetyAndSecurity","featureLabels",[],"displayLabels",[236,237,238],"policyLabels",[],"systemLabels",[],"products",[],"hasNimMetadata",{"_204":251,"_240":252,"_242":253,"_244":245},{"_204":248,"_240":249,"_242":250,"_244":245},{"_204":239,"_240":241,"_242":243,"_244":245},"DL","value","soln_dl","filter",{"_246":247,"_240":241},"category","label","field","technology","Computer Vision","soln_computer_vision",{"_246":247,"_240":249},"AI","soln_ai",{"_246":247,"_240":252},{"_107":1233,"_109":1234},"ngcApps",[1186],"csaApiBaseUrl","https://www.nvidia.com/ai-agents/csa-agent/dcsm","datadogRum",{"_1167":1168,"_1169":1170,"_1171":1172,"_1173":1174,"_1175":265,"_138":289,"_1176":1177,"_1178":55,"_1179":86,"_1180":86,"_1181":1182,"_1183":86,"_1184":1185},"amplitude",{"_1164":1165,"_801":-7,"_1166":30},"disableJs","environment","prod","featureFlagsBlob","JTdCJTIydGVzdEZsYWclMjIlM0FmYWxzZSUyQyUyMnNob3dTZWFyY2hMYWJlbFNldEZpbHRlcnMlMjIlM0FmYWxzZSUyQyUyMmVuYWJsZUNzYVdpZGdldCUyMiUzQWZhbHNlJTJDJTIyZW5hYmxlUHJvZHVjdEdyb3VwaW5nQnlTdWJzY3JpcHRpb24lMjIlM0FmYWxzZSUyQyUyMmNvbnRhaW5lclNjYW5uaW5nUmVkZXNpZ25NMSUyMiUzQXRydWUlN0Q=","featureFlagsGuarded","isDevLikeEnv","isPlaywright","isMobileDevice","categorizedOrgs",{"_1158":1159,"_1160":1161,"_1162":1163},"currentOrgContext","currentContextRoles",[],"enterpriseOrgs",[],"locale","en","ngcApiOrigin","ngcHelmOrigin","origin","https://catalog.ngc.nvidia.com","usesMocks","theme","year",2026,"1.10.0","defaultSearchSuggestions",{"_1041":178,"_1042":1043,"_1044":1045,"_1046":1047},"announcements",[],"consentState",{"_327":1031,"_1032":30,"_1033":30,"_1034":86,"_1035":1036},"consentConfig",{"_309":310,"_311":312,"_313":314,"_315":316,"_317":318,"_319":320,"_321":322,"_323":324,"_325":326,"_327":328},"showContactAdmin",1785226801970,[],[],[303,304,305,306,307,308],{"_44":59,"_46":70,"_48":102,"_50":-5,"_52":-5,"_54":55},{"_44":59,"_46":68,"_48":102,"_50":-5,"_52":-5,"_54":55},{"_44":59,"_46":66,"_48":102,"_50":-5,"_52":-5,"_54":55},{"_44":59,"_46":60,"_48":102,"_50":-5,"_52":-5,"_54":55},{"_44":56,"_46":57,"_48":49,"_50":51,"_52":58,"_54":55},{"_44":45,"_46":47,"_48":49,"_50":51,"_52":53,"_54":55},"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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