Tweak to README

Signed-off-by: Christopher Bridge <[email protected]>

Author: Christopher Bridge

integrations/nuance_pin/README.md

@@ -30,8 +30,7 @@ cd integrations/nuance_pin
 In this folder you will see the following directory structure
 ```bash
 nuance_pin
-    ├── app/                    # directory with MONAI app code
-    ├── lib/                    # you should create this directory where we will place Nuance PIN wheels
+    ├── app/                    # directory with MONAI app code ├── lib/                    # you should create this directory where we will place Nuance PIN wheels
     ├── model/                  # directory where we will place the model used by our MONAI app
     ├── app_wrapper.py          # Nuance PIN wrapper code
     ├── docker-compose.yml      # docker compose runtime script
@@ -136,12 +135,12 @@ python -m AiSvcTest -i ~/Downloads/dcm -o ~/Downloads/dcm/out -s http://localhos
 
 ### Bring Your Own MONAI App
 
-This example integration may be modified to fit any existing MONAI app, however, there may be caveats.
+This example integration may be modified to fit any existing MONAI app by tailoring the files within the `app/` directory, however, there may be caveats.
 
 Nuance PIN requires all artifacts present in the output folder to be also added into the `resultManifest.json` output file
 to consider the run successful. To see what this means in practical terms, check the `resultManifest.json` output from the
 example app we ran the in previous sections. You will notice an entry in `resultManifest.json` that corresponds to the DICOM
-SEG output generated by the underlying MONAI app
+GSPS output generated by the underlying MONAI app
 ```json
   "study": {
     "uid": "1.2.826.0.1.3680043.2.1125.1.67295333199898911264201812221946213",
@@ -153,17 +152,16 @@ SEG output generated by the underlying MONAI app
           {
             "documentType": "application/dicom",
             "groupCode": "default",
-            "name": "dicom_seg-DICOMSEG.dcm",
+            "name": "gsps.dcm",
             "trackingUids": []
           }
         ]
       }
     ]
   },
 ```
-This entry is generated by `app_wrapper.py`, which takes care of adding any DICOM present in the output folder in the `resultManifest.json`
-to ensure that existing MONAI apps complete successfully when deployed in Nuance. In general, however, the developer may need to tailor some
-of the code in `app_wrapper.py` to provide more insight to Nuance's network, such as adding findings, conclusions, etc. and generating more insight
+This entry is generated automatically by Nuance's `ai_service` library as a result of uploading the DICOM GSPS object in `app/post_inference_ops.py`.
+In general, however, the developer may need to tailor some of the code in `app_wrapper.py` to provide more insight to Nuance's network, such as adding findings, conclusions, etc. and generating more insight
 using SNOMED codes. All of this is handled within the Nuance PIN SDK libraries - for more information please consult Nuance PIN [documentation](https://www.nuance.com/healthcare/diagnostics-solutions/precision-imaging-network.html).
 
 In simpler cases, the developer will need to place their code and model under `nuance_pin`. Placing the model under `model` is optional as the model may be placed