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HoVerNet tutorial (#1027)
Fixes [#4882.](Project-MONAI/MONAI#4882) ### Description A torch version tutorial for HoVerNet training pipeline. ### Checks <!--- Put an `x` in all the boxes that apply, and remove the not applicable items --> - [ ] Notebook runs automatically `./runner [-p <regex_pattern>]` Signed-off-by: KumoLiu <[email protected]>
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README.md

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@@ -177,12 +177,16 @@ An example of Multiple Instance Learning (MIL) classification from Whole Slide I
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##### [NuClick Annotation](./pathology/nuclick#nuclick-interaction-model)
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The notebook demonstrates examples of training and inference pipelines with interactive annotation for pathology, NuClick is used for delineating nuclei, cells and a squiggle for outlining glands.
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#### [HoVerNet:Nuclear segmentation and classification task](./pathology/hovernet)
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This tutorial demonstrates how to construct a training workflow of [HoVerNet](https://www.sciencedirect.com/science/article/abs/pii/S1361841519301045) on nuclear segmentation and classification task using the CoNSep dataset.
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##### [Nuclei Classification](./pathology/nuclick#nuclei-classification-model)
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The notebook demonstrates examples of training and inference pipelines with interactive annotation for pathology, NuClick is used for delineating nuclei, cells and a squiggle for outlining glands.
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#### <ins>**Acceleration**</ins>
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##### [fast_model_training_guide](./acceleration/fast_model_training_guide.md)
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The document introduces details of how to profile the training pipeline, how to analyze the dataset and select suitable algorithms, and how to optimize GPU utilization in single GPU, multi-GPUs or even multi-nodes.
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##### [distributed_training](./acceleration/distributed_training)
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The examples show how to execute distributed training and evaluation based on 3 different frameworks:
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- PyTorch native `DistributedDataParallel` module with `torch.distributed.launch`.

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