Merge pull request #5 from AdaptiveMotorControlLab/Cyril_repo_June25

from dev repo; merge into Main
- + some minor doc changes
Co-authored-by: @C-Achard

Author: MMathisLab

docs/res/guides/detailed_walkthrough.rst

@@ -119,11 +119,11 @@ Finally, the last tab lets you choose :
 * The models
 
     * SegResNet is a lightweight model (low memory requirements) from MONAI originally designed for 3D fMRI data.
-    * VNet is a heavier (than SegResNet) CNN from MONAI designed for medical image segmentation.
+    * VNet is a larger (than SegResNet) CNN from MONAI designed for medical image segmentation.
     * TRAILMAP is our PyTorch implementation of a 3D CNN model trained for axonal detection in cleared tissue.
-    * TRAILMAP-MS is our implementation in PyTorch additionally trained on mouse cortical neural nuclei from mesoSPIM data.
+    * TRAILMAP_MS is our implementation in PyTorch additionally trained on mouse cortical neural nuclei from mesoSPIM data.
     * Note, the code is very modular, so it is relatively straightforward to use (and contribute) your model as well.
-    
+
 
 * The loss : for object detection in 3D volumes you'll likely want to use the Dice or Dice-focal Loss.
 

docs/res/guides/inference_module_guide.rst

@@ -13,8 +13,8 @@ Model            Link to original paper
 ==============   ================================================================================================
 VNet             `Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation`_
 SegResNet        `3D MRI brain tumor segmentation using autoencoder regularization`_
-TRAILMAP_test     An emulation of the `TRAILMAP project on GitHub`_ using a custom copy in Pytorch
-TRAILMAP          An emulation of the `TRAILMAP project on GitHub`_ using `3DUnet for Pytorch`_
+TRAILMAP_MS       A PyTorch implementation of the `TRAILMAP project on GitHub`_ pretrained with MesoSpim data
+TRAILMAP          An implementation of the `TRAILMAP project on GitHub`_ using a `3DUNet for PyTorch`_
 ==============   ================================================================================================
 
 .. _Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation: https://arxiv.org/pdf/1606.04797.pdf

docs/res/guides/training_module_guide.rst

@@ -13,8 +13,8 @@ Model            Link to original paper
 ==============   ================================================================================================
 VNet             `Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation`_
 SegResNet        `3D MRI brain tumor segmentation using autoencoder regularization`_
-TRAILMAP_test     An emulation of the `TRAILMAP project on GitHub`_ using a custom copy in Pytorch
-TRAILMAP          An emulation of the `TRAILMAP project on GitHub`_ using `3DUnet for Pytorch`_
+TRAILMAP_MS       A PyTorch implementation of the `TRAILMAP project on GitHub`_ pretrained with MesoSpim data
+TRAILMAP          An implementation of the `TRAILMAP project on GitHub`_ using a `3DUNet for PyTorch`_
 ==============   ================================================================================================
 
 .. _Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation: https://arxiv.org/pdf/1606.04797.pdf
@@ -120,4 +120,3 @@ Source code
 * :doc:`../code/plugin_model_training`
 * :doc:`../code/model_framework`
 * :doc:`../code/model_workers`
-

napari_cellseg3d/__init__.py

@@ -1 +1 @@
-__version__ = "0.0.1"
+__version__ = "0.0.3"