Upload maisi_ct_generative version 1.0.2

configs/metadata.json

@@ -1,7 +1,8 @@
 {
     "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_generator_ldm_20240318.json",
-    "version": "1.0.1",
+    "version": "1.0.2",
     "changelog": {
+        "1.0.2": "enhance metadata with improved descriptions and intended use",
         "1.0.1": "add missing dependencies",
         "1.0.0": "accelerated maisi, inference only, is not compartible with previous maisi diffusion model weights",
         "0.4.6": "add TensorRT support",
@@ -29,17 +30,19 @@
     "supported_apps": {
         "maisi-nim": ""
     },
-    "name": "CT image latent diffusion generation",
-    "task": "CT image synthesis",
-    "description": "A generative model for creating 3D CT from Gaussian noise",
-    "authors": "MONAI team",
+    "name": "MAISI: Medical AI for Synthetic Imaging",
+    "task": "Synthetic 3D CT Image Generation with Anatomical Control",
+    "description": "MAISI is a diffusion-based model for generating synthetic 3D CT images with anatomical control. The model produces realistic CT volumes up to 512\u00d7512\u00d7768 voxels and can generate images conditioned on organ segmentations of 127 anatomical structures.",
+    "authors": "MONAI Team",
     "copyright": "Copyright (c) MONAI Consortium",
     "data_source": "http://medicaldecathlon.com/",
     "data_type": "nibabel",
     "image_classes": "Flair brain MRI with 1.1x1.1x1.1 mm voxel size",
     "eval_metrics": {},
     "intended_use": "This is a research tool/prototype and not to be used clinically",
-    "references": [],
+    "references": [
+        "Guo, Pengfei, et al. 'MAISI: Medical AI for Synthetic Imaging.' arXiv preprint arXiv:2409.11169 (2024)."
+    ],
     "autoencoder_data_format": {
         "inputs": {
             "image": {