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brats_mri_segmentation

monai
medical
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update error links

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  1. README.md +2 -2
  2. configs/metadata.json +2 -1
  3. docs/README.md +2 -2
README.md CHANGED
@@ -6,7 +6,7 @@ library_name: monai
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  license: apache-2.0
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  ---
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  # Model Overview
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- A pre-trained model for volumetric (3D) segmentation of brain tumor subregions from multimodal MRIs based on BraTS 2018 data. The whole pipeline is modified from [clara_pt_brain_mri_segmentation](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/med/models/clara_pt_brain_mri_segmentation).
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  The model is trained to segment 3 nested subregions of primary brain tumors (gliomas): the "enhancing tumor" (ET), the "tumor core" (TC), the "whole tumor" (WT) based on 4 aligned input MRI scans (T1c, T1, T2, FLAIR).
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  - The ET is described by areas that show hyper intensity in T1c when compared to T1, but also when compared to "healthy" white matter in T1c.
@@ -16,7 +16,7 @@ The model is trained to segment 3 nested subregions of primary brain tumors (gli
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  ![Model workflow](https://developer.download.nvidia.com/assets/Clara/Images/clara_pt_brain_mri_segmentation_workflow.png)
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  ## Data
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- The training data is from the [Multimodal Brain Tumor Segmentation Challenge (BraTS) 2018](https://www.med.upenn.edu/cbica/sbia/brats2018/tasks.html).
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  - Target: 3 tumor subregions
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  - Task: Segmentation
 
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  license: apache-2.0
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  ---
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  # Model Overview
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+ A pre-trained model for volumetric (3D) segmentation of brain tumor subregions from multimodal MRIs based on BraTS 2018 data.
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  The model is trained to segment 3 nested subregions of primary brain tumors (gliomas): the "enhancing tumor" (ET), the "tumor core" (TC), the "whole tumor" (WT) based on 4 aligned input MRI scans (T1c, T1, T2, FLAIR).
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  - The ET is described by areas that show hyper intensity in T1c when compared to T1, but also when compared to "healthy" white matter in T1c.
 
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  ![Model workflow](https://developer.download.nvidia.com/assets/Clara/Images/clara_pt_brain_mri_segmentation_workflow.png)
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  ## Data
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+ The training data is from the [Multimodal Brain Tumor Segmentation Challenge (BraTS) 2018](https://www.med.upenn.edu/sbia/brats2018.html).
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  - Target: 3 tumor subregions
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  - Task: Segmentation
configs/metadata.json CHANGED
@@ -1,7 +1,8 @@
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  {
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  "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220324.json",
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- "version": "0.4.3",
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  "changelog": {
 
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  "0.4.3": "add the ONNX-TensorRT way of model conversion",
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  "0.4.2": "fix mgpu finalize issue",
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  "0.4.1": "add non-deterministic note",
 
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  {
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  "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220324.json",
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+ "version": "0.4.4",
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  "changelog": {
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+ "0.4.4": "update error links",
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  "0.4.3": "add the ONNX-TensorRT way of model conversion",
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  "0.4.2": "fix mgpu finalize issue",
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  "0.4.1": "add non-deterministic note",
docs/README.md CHANGED
@@ -1,5 +1,5 @@
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  # Model Overview
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- A pre-trained model for volumetric (3D) segmentation of brain tumor subregions from multimodal MRIs based on BraTS 2018 data. The whole pipeline is modified from [clara_pt_brain_mri_segmentation](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/med/models/clara_pt_brain_mri_segmentation).
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  The model is trained to segment 3 nested subregions of primary brain tumors (gliomas): the "enhancing tumor" (ET), the "tumor core" (TC), the "whole tumor" (WT) based on 4 aligned input MRI scans (T1c, T1, T2, FLAIR).
5
  - The ET is described by areas that show hyper intensity in T1c when compared to T1, but also when compared to "healthy" white matter in T1c.
@@ -9,7 +9,7 @@ The model is trained to segment 3 nested subregions of primary brain tumors (gli
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  ![Model workflow](https://developer.download.nvidia.com/assets/Clara/Images/clara_pt_brain_mri_segmentation_workflow.png)
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  ## Data
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- The training data is from the [Multimodal Brain Tumor Segmentation Challenge (BraTS) 2018](https://www.med.upenn.edu/cbica/sbia/brats2018/tasks.html).
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  - Target: 3 tumor subregions
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  - Task: Segmentation
 
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  # Model Overview
2
+ A pre-trained model for volumetric (3D) segmentation of brain tumor subregions from multimodal MRIs based on BraTS 2018 data.
3
 
4
  The model is trained to segment 3 nested subregions of primary brain tumors (gliomas): the "enhancing tumor" (ET), the "tumor core" (TC), the "whole tumor" (WT) based on 4 aligned input MRI scans (T1c, T1, T2, FLAIR).
5
  - The ET is described by areas that show hyper intensity in T1c when compared to T1, but also when compared to "healthy" white matter in T1c.
 
9
  ![Model workflow](https://developer.download.nvidia.com/assets/Clara/Images/clara_pt_brain_mri_segmentation_workflow.png)
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  ## Data
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+ The training data is from the [Multimodal Brain Tumor Segmentation Challenge (BraTS) 2018](https://www.med.upenn.edu/sbia/brats2018.html).
13
 
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  - Target: 3 tumor subregions
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  - Task: Segmentation