update to use monai 1.0.1

README.md

@@ -17,7 +17,7 @@ The model is trained to segment 3 nested subregions of primary brain tumors (gli
 
 ## Data
 
-The training data is from the [Multimodal Brain Tumor Segmentation Challenge (BraTS) 2018](https://www.med.upenn.edu/sbia/brats2018/data.html).
+The training data is from the [Multimodal Brain Tumor Segmentation Challenge (BraTS) 2018](https://www.med.upenn.edu/cbica/sbia/brats2018/tasks.html).
 
 - Target: 3 tumor subregions
 - Task: Segmentation

configs/evaluate.json

@@ -23,7 +23,7 @@
                 "threshold": 0.5
             },
             {
-                "_target_": "SplitChanneld",
+                "_target_": "SplitDimd",
                 "keys": [
                     "pred",
                     "label"

configs/metadata.json

@@ -1,7 +1,8 @@
 {
     "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220324.json",
-    "version": "0.3.2",
+    "version": "0.3.3",
     "changelog": {
+        "0.3.3": "update to use monai 1.0.1",
         "0.3.2": "enhance readme on commands example",
         "0.3.1": "fix license Copyright error",
         "0.3.0": "update license files",
@@ -10,12 +11,14 @@
         "0.1.1": "update for MetaTensor",
         "0.1.0": "complete the model package"
     },
-    "monai_version": "0.9.1",
-    "pytorch_version": "1.12.0",
+    "monai_version": "1.0.1",
+    "pytorch_version": "1.13.0",
     "numpy_version": "1.22.4",
     "optional_packages_version": {
         "nibabel": "4.0.1",
-        "pytorch-ignite": "0.4.9"
+        "pytorch-ignite": "0.4.9",
+        "scikit-learn": "1.1.3",
+        "tensorboard": "2.10.1"
     },
     "task": "Multimodal Brain Tumor segmentation",
     "description": "A pre-trained model for volumetric (3D) segmentation of brain tumor subregions from multimodal MRIs based on BraTS 2018 data",

configs/train.json

@@ -248,7 +248,7 @@
                     "threshold": 0.5
                 },
                 {
-                    "_target_": "SplitChanneld",
+                    "_target_": "SplitDimd",
                     "keys": [
                         "pred",
                         "label"

docs/README.md

@@ -10,7 +10,7 @@ The model is trained to segment 3 nested subregions of primary brain tumors (gli
 
 ## Data
 
-The training data is from the [Multimodal Brain Tumor Segmentation Challenge (BraTS) 2018](https://www.med.upenn.edu/sbia/brats2018/data.html).
+The training data is from the [Multimodal Brain Tumor Segmentation Challenge (BraTS) 2018](https://www.med.upenn.edu/cbica/sbia/brats2018/tasks.html).
 
 - Target: 3 tumor subregions
 - Task: Segmentation