diff --git a/docs/faq.rst b/docs/faq.rst
index 7687785..8dce6bf 100644
--- a/docs/faq.rst
+++ b/docs/faq.rst
@@ -16,3 +16,15 @@ FAQ
     Please ensure TMPDIR has execution permissions or temporarily set TMPDIR to a directory that does::
 
         TMPDIR=. pip install scallops
+
+#. Unable to download model for Stardist or other deep learning models
+    Some workflow environments (e.g. AWS HealthOmics) prohibit accesssing public websites.
+    You need to download model files to an accessible location, and set the workflow input, `model_dir`
+    to this location.
+
+    Example::
+
+        wget https://github.com/stardist/stardist-models/releases/download/v0.1/python_2D_versatile_fluo.zip
+        aws s3 cp python_2D_versatile_fluo.zip s3://my-bucket/model/
+
+    In your OPS workflow input JSON, set `model_dir` to `s3://my-bucket/model/`
diff --git a/docs/workflows.rst b/docs/workflows.rst
index a106059..66b880e 100644
--- a/docs/workflows.rst
+++ b/docs/workflows.rst
@@ -24,9 +24,9 @@ Workflow Steps
 3.  **Stitching**:
 
     * Applies the calculated flatfield to the raw tiles.
-    * Corrects for radial distortion (can be disabled or `k` can be provided).
+    * Corrects for radial distortion.
     * Aligns tiles using stage positions and cross-correlation.
-    * Stitches tiles into a multi-scale OME-Zarr image.
+    * Stitches tiles into an OME-Zarr image.
 
 Inputs
 ------
@@ -45,13 +45,16 @@ These are the absolute minimum parameters required to run the stitching workflow
      - Description
    * - **urls**
      - Array[String]
-     - List of directories containing raw images (S3 or local paths).
+     - List of directories containing raw images (e.g S3 URLs).
    * - **image_pattern**
      - String
      - Regex-like pattern to parse filenames (e.g., ``"Well{well}_Point{point}.nd2"``).
    * - **output_directory**
      - String
      - Base path for outputs.
+   * - **docker**
+     - String
+     - Workflow docker image.
 
 .. code-block:: json
    :caption: Minimal Stitching JSON
@@ -59,7 +62,8 @@ These are the absolute minimum parameters required to run the stitching workflow
    {
       "urls": ["s3://your-bucket/experiment_data/"],
       "image_pattern": "20231010_10x_6W_SBS_c{t}/plate{plate}/Well{well}_Point{skip}_{skip}_Channel{skip}_Seq{skip}.nd2",
-      "output_directory": "s3://your-bucket/experiment_data/stitch/iss/"
+      "output_directory": "s3://your-bucket/experiment_data/stitch/iss/",
+      "docker":"772311241819.dkr.ecr.us-west-2.amazonaws.com/scallops:1.0.0"
    }
 
 Full Parameter Reference (Advanced)
@@ -118,7 +122,7 @@ Below is the complete list of exposed options, including optional settings for g
      - Force re-run of stitching even if output exists.
    * - **Resources**
      - Various
-     - ``stitch_cpu``, ``stitch_memory``, ``stitch_disks``, etc. can be set to override defaults.
+     - ``stitch_cpu``, ``stitch_memory``, etc. can be set to override defaults.
 
 Outputs
 -------
@@ -186,6 +190,9 @@ These are the absolute minimum parameters required to run the OPS workflow.
    * - **reads_labels**
      - String
      - Which segmentation label to assign reads to (e.g., ``"cell"`` or ``"nuclei"``).
+   * - **docker**
+     - String
+     - Workflow docker image.
 
 .. code-block:: json
    :caption: Minimal OPS JSON
@@ -196,7 +203,8 @@ These are the absolute minimum parameters required to run the OPS workflow.
       "phenotype_url": "s3://your-bucket/experiment/stitch/pheno/stitch/stitch.zarr/",
       "phenotype_dapi_channel": 4,
       "phenotype_cyto_channel": [6],
-      "reads_labels": "cell"
+      "reads_labels": "cell",
+      "docker":"772311241819.dkr.ecr.us-west-2.amazonaws.com/scallops:1.0.0"
    }
 
 Full Parameter Reference (Advanced)
@@ -225,9 +233,6 @@ Below is the complete list of exposed options covering registration, feature ext
    * - **subset**
      - Array[String]
      - Filter specific wells/plates.
-   * - **batch_size**
-     - Int
-     - Number of groups to process in one batch.
 
 **Segmentation & Registration**
 
@@ -313,7 +318,7 @@ Below is the complete list of exposed options covering registration, feature ext
      - Array[Float]
      - Sigma for Laplacian of Gaussian spot detection.
 
-**Control Flags (Force / Skip)**
+**Additional Parameters**
 
 .. list-table::
    :widths: 30 15 55
@@ -322,19 +327,21 @@ Below is the complete list of exposed options covering registration, feature ext
    * - Parameter
      - Type
      - Description
-   * - **run_spot_detect**
-     - Boolean
-     - Default ``true``.
-   * - **run_nuclei_segmentation**
-     - Boolean
-     - Default ``true``.
-   * - **run_cell_segmentation**
+   * - **model_dir**
+     - String
+     - Path containing deep learning model resouces (See :doc:`FAQ <faq>` for more details.)
+   * - **run_``task``**
      - Boolean
-     - Default ``true``.
-   * - **force_merge**
+     - Set to ``false``, (e.g. run_nuclei_segmentation) to skip task
+   * - **force_``task``**
      - Boolean
-     - Force re-merge even if output exists.
-
+     - Set to ``true``, to re-run task (e.g. force_segment_cell) even if output exists.
+   * - **Resources**
+     - Various
+     - ``segment_nuclei_cpu``, ``segment_nuclei_memory``, etc. can be set to override defaults.
+   * - **batch_size**
+     - Int
+     - Number of groups to process in one batch.
 Outputs
 -------
 
@@ -396,8 +403,7 @@ Create a JSON file (e.g., ``ops_input.json``) defining your inputs. Below is a m
       "segment_cell_threshold_correction_factor": 1.0,
       "cell_segmentation_extra_arguments": "--closing-radius 5",
 
-      "docker_registry": "123456789012.dkr.ecr.us-region-1.amazonaws.com",
-      "docker_version": "latest"
+      "docker": "123456789012.dkr.ecr.us-region-1.amazonaws.com/scallops:latest"
     }
 
 Step 2: Run with miniwdl-omics-run
@@ -451,7 +457,7 @@ Suppose you only need to perform image registration without the full segmentatio
             String moving_image
             String fixed_image
             String output_dir
-            String docker_registry
+            String docker
         }
 
         # Call the existing Scallops registration task
@@ -462,7 +468,7 @@ Suppose you only need to perform image registration without the full segmentatio
                 transform_output_directory = output_dir + "/transforms",
                 moving_output_directory = output_dir + "/registered_images",
                 # Pass through required runtime parameters
-                docker = docker_registry + "/scallops:latest",
+                docker = docker,
                 cpu = 4,
                 memory = "16 GiB",
                 # ... (other required inputs like zones, disks, etc.)
diff --git a/scallops/tests/test_wdl.py b/scallops/tests/test_wdl.py
index c7a3c7a..64e4279 100644
--- a/scallops/tests/test_wdl.py
+++ b/scallops/tests/test_wdl.py
@@ -55,6 +55,7 @@ def test_stitch_wdl_z_stack(tmp_path):
         "z_index": "focus",
         "stitch_radial_correction_k": "none",
         "output_directory": str(tmp_path / "out"),
+        "docker": "",
     }
 
     with open(tmp_path / "inputs.json", "wt") as out:
@@ -99,6 +100,7 @@ def test_stitch_wdl(tmp_path):
         "stitch_workflow.urls": [str(input_path)],
         "stitch_workflow.image_pattern": "{well}-{skip}.zarr",
         "stitch_workflow.output_directory": str(tmp_path / "out"),
+        "stitch_workflow.docker": "",
     }
 
     with open(tmp_path / "inputs.json", "wt") as out:
@@ -176,6 +178,7 @@ def test_ops_wdl(tmp_path):
         "ops_workflow.mark_stitch_boundary_cells": False,
         "ops_workflow.reads_labels": "cell",
         "ops_workflow.merge_extra_arguments": "--format parquet",
+        "ops_workflow.docker": "",
     }
 
     with open(tmp_path / "inputs.json", "wt") as out:
diff --git a/wdl/ops_workflow.wdl b/wdl/ops_workflow.wdl
index 294fd62..576cf33 100644
--- a/wdl/ops_workflow.wdl
+++ b/wdl/ops_workflow.wdl
@@ -64,7 +64,7 @@ workflow ops_workflow {
         String? reads_threshold_peaks_crosstalk
         String? reads_extra_arguments
 
-        String model_dir = "s3://bigdipir-ctg-s3/models/"
+        String model_dir = ""
 
         # nuclei segment
         String? nuclei_segmentation
@@ -151,11 +151,11 @@ workflow ops_workflow {
         String cell_intersects_boundary_disks = "local-disk 200 HDD"
 
 
-        String docker = "563221710766.dkr.ecr.us-west-2.amazonaws.com/external/ctg/scallops:latest"
+        String docker
 
         Int preemptible = 0
         String zones = "us-west1-a us-west1-b us-west1-c"
-        String aws_queue_arn = "arn:aws:batch:us-west-2:752311211819:job-queue/gred"
+        String aws_queue_arn = ""
         Int max_retries = 0
 
         String segment_suffix = "segment.zarr"
diff --git a/wdl/stitch_workflow.wdl b/wdl/stitch_workflow.wdl
index 2a6710f..79a7e31 100644
--- a/wdl/stitch_workflow.wdl
+++ b/wdl/stitch_workflow.wdl
@@ -42,11 +42,11 @@ workflow stitch_workflow {
         Boolean? force_illumination_correction
         Boolean? force_stitch
 
-        String docker = "563221710766.dkr.ecr.us-west-2.amazonaws.com/external/ctg/scallops:latest"
+        String docker
 
         Int preemptible = 0
         String zones = "us-west1-a us-west1-b us-west1-c"
-        String aws_queue_arn = "arn:aws:batch:us-west-2:752311211819:job-queue/gred"
+        String aws_queue_arn = ""
         Int max_retries = 0
 
     }