You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Copy file name to clipboardExpand all lines: docs/about/release-notes.md
+29Lines changed: 29 additions & 0 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -1,6 +1,35 @@
1
1
# Release Notes
2
2
3
3
4
+
## ShapeWorks 6.7.0
5
+
6
+
### What is new?
7
+
8
+
***ShapeWorks Back-end**
9
+
* Fixed domain optimization speedups: shape space precomputation, Procrustes caching, and batch particle loading
10
+
* PCA projection correspondence for fixed domain optimization (`use_pca_projection` parameter)
11
+
* Automatic mesh repair in grooming pipeline (replaces manual Extract Largest Component step)
12
+
* Auto ICP alignment subset size defaults to 30 shapes for faster grooming on large datasets
13
+
* Support for multiple shared boundaries between domains
14
+
* Early stopping via morphological deviation score for optimization convergence detection
15
+
* DeepSSM CLI: `shapeworks deepssm` command for headless/batch DeepSSM workflows
16
+
* Laplacian mesh warping as alternative to biharmonic, reducing thinning artifacts on sparse regions
17
+
* Built-in performance profiling and Chrome trace output via `SW_TIME_PROFILE` and `SW_TIME_TRACE` environment variables (see [developer docs](../dev/build.md#performance-profiling))
18
+
19
+
***ShapeWorks Front-end**
20
+
* DWD (Distance Weighted Discrimination) group analysis method alongside LDA
21
+
* Redesigned Optimize panel
22
+
* Export clipped meshes
23
+
* Warp method selector (Biharmonic/Laplacian) in Analysis panel
24
+
25
+
***Platform Updates**
26
+
* Python 3.12
27
+
* VTK 9.5.0
28
+
* ITK 5.4.4
29
+
* PyTorch 2.8.0 (2.2.2 on Intel Mac)
30
+
* Linux builds use manylinux_2_28 (GLIBC 2.28, compatible with RHEL 8+, Ubuntu 20.04+)
The `shapeworks deepssm` command runs the full DeepSSM pipeline from the command line, without requiring Studio. This enables headless execution on HPC clusters and servers, batch processing of multiple projects, and integration with shell scripts and automated workflows.
70
+
71
+
### Command Syntax
72
+
73
+
```bash
74
+
shapeworks deepssm <project_file> [options]
75
+
```
76
+
77
+
The project file (`.xlsx` or `.swproj`) must contain both image and shape columns (e.g., `shape_la`, `image_mri`), along with DeepSSM parameters such as data split percentages, augmentation settings, and training configuration. These are the same parameters configurable in the [DeepSSM Studio module](../studio/deepssm-in-studio.md).
78
+
79
+
### Options
80
+
81
+
| Option | Description |
82
+
|--------|-------------|
83
+
|`--name <file>`| Path to project file (alternative to positional argument) |
84
+
|`--all`| Run all four steps: prep, augment, train, test |
85
+
|`--prep <step>`| Run preparation. Steps: `all`, `groom_training`, `optimize_training`, `optimize_validation`, `groom_images`|
86
+
|`--augment`| Run data augmentation |
87
+
|`--train`| Run model training |
88
+
|`--test`| Run testing/inference |
89
+
|`--num_workers <n>`| Number of PyTorch data loader workers (default: 0) |
90
+
|`--aug_processes <n>`| Number of augmentation processes (default: 0 = use all cores) |
91
+
92
+
If none of `--prep`, `--augment`, `--train`, `--test`, or `--all` are specified, all four steps are run by default.
93
+
94
+
### Examples
95
+
96
+
Run the full pipeline:
97
+
98
+
```bash
99
+
shapeworks deepssm my_project.swproj --all
100
+
```
101
+
102
+
Run only preparation and augmentation:
103
+
104
+
```bash
105
+
shapeworks deepssm my_project.swproj --prep all --augment
106
+
```
107
+
108
+
Run just training and testing with 4 data loader workers:
The four steps correspond to the same stages available in [DeepSSM in Studio](../studio/deepssm-in-studio.md):
123
+
124
+
1.**Prep** — Grooms and optimizes training shapes, generates validation particles using fixed domains, and prepares images. The `--prep` flag accepts a sub-step to run only part of the preparation.
125
+
2.**Augment** — Generates synthetic training data via PCA-based data augmentation. Use `--aug_processes` to control parallelism.
126
+
3.**Train** — Trains the DeepSSM network (Base-DeepSSM or TL-DeepSSM depending on project settings). Use `--num_workers` to set PyTorch data loader parallelism.
127
+
4.**Test** — Runs inference on the test set and evaluates predicted shapes against ground truth.
128
+
129
+
### Configuring DeepSSM Parameters
130
+
131
+
All DeepSSM parameters (data split, augmentation count, network architecture, TL-DeepSSM settings, fine-tuning, etc.) are stored in the project file. These can be configured in Studio before running via the CLI, or set programmatically using the ShapeWorks Python API. See the [training configuration parameters](#config-file-parameter-descriptions) section below for details on available settings.
132
+
67
133
## Using the DeepSSM Python Package
68
134
69
135
The ShapeWorks DeepSSM package, `DeepSSMUtils`, is installed with the rest of the ShapeWorks Anaconda environment using `install_shapeworks`.
Copy file name to clipboardExpand all lines: docs/dev/build.md
+53-1Lines changed: 53 additions & 1 deletion
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -212,4 +212,56 @@ After cmake the Visual Studio solution can be opened with `start ShapeWorks.sln`
212
212
213
213
!!! important "RelWithDebInfo only"
214
214
Currently it's only possible to build **RelWithDebInfo** on Windows.
215
-
215
+
216
+
217
+
## Performance Profiling
218
+
219
+
ShapeWorks includes a built-in profiling and tracing framework for diagnosing performance issues. It is controlled via environment variables and has zero overhead when disabled.
220
+
221
+
### Environment Variables
222
+
223
+
| Variable | Description |
224
+
|----------|-------------|
225
+
|`SW_TIME_PROFILE=on`| Enable flat profiling. Writes a summary report to `profile.txt` at shutdown with exclusive/inclusive times, call counts, and per-call averages, grouped by thread. |
226
+
|`SW_TIME_TRACE=on`| Enable Chrome trace format output. Writes `trace.json` which can be loaded in `chrome://tracing` or [Perfetto](https://ui.perfetto.dev/) for a timeline visualization. |
Copy file name to clipboardExpand all lines: docs/new/ai-assisted-segmentation.md
+2-2Lines changed: 2 additions & 2 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -5,8 +5,8 @@
5
5
6
6
[`Medical Open Network for AI (MONAI) Label`](https://monai.io/) is a deep learning framework designed for efficient annotation and segmentation of medical images.
7
7
8
-
## What’s New?
9
-
ShapeWorks Studio now integrates MONAI Label, enabling seamless access to fully automated and interactive deep learning models for segmenting radiology images across various modalities.
8
+
## Overview
9
+
ShapeWorks Studio integrates MONAI Label, enabling seamless access to fully automated and interactive deep learning models for segmenting radiology images across various modalities.
10
10
11
11
For a detailed demo and step-by-step instructions on using MONAI Label within ShapeWorks Studio, refer to the following guide:
See [DeepSSM in Studio](../studio/deepssm-in-studio.md) for more information.
11
11
12
12
## Multiple Domain Alignments
13
13
14
-
New in ShapeWorks 6.2, we have added support for multiple alignment strategies in ShapeWorks Studio. This allows analysis with and without articulation with a choice of reference domain, or global alignment.
14
+
ShapeWorks Studio supports multiple alignment strategies, allowing analysis with and without articulation with a choice of reference domain, or global alignment.
@@ -82,27 +82,25 @@ Multiple sources of crashes during mesh warping have been fixed and the overall
82
82
83
83
---
84
84
85
-
# New in ShapeWorks Studio 6.1
86
-
87
85
## Multiple Domains
88
86
89
-
As of ShapeWorks 6.1, we added support in ShapeWorks Studio for modeling multiple domains (e.g. anatomies) in joint correspondance model.
87
+
ShapeWorks Studio supports modeling multiple domains (e.g. anatomies) in a joint correspondence model.
90
88
91
89

92
90
93
91
See [Multiple Domains](../studio/multiple-domains.md) for more information.
94
92
95
93
## Mesh Grooming
96
94
97
-
As of ShapeWorks 6.1, we added support in ShapeWorks Studio for mesh grooming, including smoothing, hole filling, and iterative closest point pre-alignment.
95
+
ShapeWorks Studio supports mesh grooming, including smoothing, hole filling, and iterative closest point pre-alignment.
98
96
99
97
{: width="300" }
100
98
101
99
See [Groom Module](../studio/getting-started-with-studio.md#groom-module) for more information.
102
100
103
101
## Mesh Support
104
102
105
-
As of ShapeWorks 6.0, we added mesh support to ShapeWorks Studio including loading meshes, optimizing shape models directly on meshes, and visualizing meshes with scalar feature values. Meshes can store values at vertices such as "cortical thickness", or "fibrosis” and ShapeWorks Studio uses them in a similar manner as feature maps/volumes.
103
+
ShapeWorks Studio supports loading meshes, optimizing shape models directly on meshes, and visualizing meshes with scalar feature values. Meshes can store values at vertices such as “cortical thickness” or “fibrosis”, which Studio uses in a similar manner as feature maps/volumes.
106
104
107
105
*Open meshes in Studio*
108
106

@@ -119,7 +117,7 @@ We also added a new surface reconstruction method with support for both mesh or
119
117
120
118
## Improved Studio Interface
121
119
122
-
As of ShapeWorks 6.0, we added support for automatic glyph sizing, draging/dropping of images and meshes. Scalar bar color is now opposite of background color (e.g., when background is white, text should be dark) (user request).
120
+
ShapeWorks Studio supports automatic glyph sizing and drag/drop of images and meshes. Scalar bar color is opposite of the background color for better contrast.
123
121
124
122
*Samples names color is opposite of the background color for a better contrast*
0 commit comments