update

docs/source/contributor_guide.rst

@@ -28,32 +28,26 @@ This repository uses a *pyproject.toml* file to specify all the requirements.
 
     All output cells in the notebooks are automatically cleared, and only cleared notebooks should be added to the repository.
 
-**mrpro/src**
-    Main code for this package
-
 **tests**
     Tests which are automatically run by pytest.
     The subfolder structure should follow the same structure as in *mrpro/src*.
 
-
-src/mrpro structure
-===================
-**algorithms**
+**src/mrpro/algorithms**
     Everything which does something with the data, e.g. prewhiten k-space or remove oversampling.
 
-**data**
+**src/mrpro/data**
     All the data classes such as ``KData``, ``ImageData`` or ``CsmData``.
     As the name suggestions these should mainly contain data and meta information.
     Any functionality beyond what is absolutely required for the classes should be put as separate functions.
 
-**operators**
+**src/mrpro/operators**
     Linear and non-linear algorithms describing e.g. the transformation from image to k-space (``FourierOp``), the
     effect of receiver coils (``SensitivityOp``) or MR signal models.
 
-**phantoms**
+**src/mrpro/phantoms**
     Numerical phantoms useful to evaluate reconstruction algorithms.
 
-**utils**
+**src/mrpro/utils**
     Utilities such as spatial filters and also more basic functionality such as applying functions serially along the
     batch dimension (``smap``).
 

docs/source/index.rst

@@ -4,20 +4,23 @@
    :align: center
    :width: 300
 
+.. |colab-badge| image:: https://colab.research.google.com/assets/colab-badge.svg
+    :target: https://colab.research.google.com/github/PTB-MR/mrpro
+
 Welcome to MRpro's documentation!
 =================================
 
 MR image reconstruction and processing package for PyTorch
 
 | **Source code:** `<https://github.com/PTB-MR/mrpro>`_
 | **Bug reports:** `<https://github.com/PTB-MR/mrpro/issues>`_
-| **Try it out:** `Open in Colab <https://colab.research.google.com/github/PTB-MR/mrpro>`_
+| **Try it out:** |colab-badge|
 | **See our examples:** :doc:`examples`
 
 Main Features
 -------------
-- **ISMRMRD support**
-  MRpro supports the ISMRMRD format for MR raw data.
+- **Standard file formats**
+  MRpro supports the ISMRMRD format for MR raw data and DICOM for image data
 
 - **PyTorch integration**
   All data containers utilize PyTorch tensors to ensure easy integration with PyTorch-based network schemes.

docs/source/user_guide.rst

@@ -49,7 +49,7 @@ Reading in raw data from a MRD file works by creating a `mrpro.data.KData` objec
 To ensure the trajectory is calculated correctly, a `~mrpro.data.traj_calculators.KTrajectoryCalculator` needs to be provided.
 The trajectory can either be calculated based on MRpro functionality (e.g. for a 2D radial sampling scheme), read out
 from MRD or calculated from a `pulseq <http://pulseq.github.io/>`_ file. See `~mrpro.data.traj_calculators`
-for available trajectory calculators.
+for available trajectory calculators and :doc:`_notebooks/comparison_trajectory_calculators` an example.
 
 
 .. note::
@@ -97,7 +97,7 @@ See for examples  :doc:`_notebooks/cartesian_reconstruction`, :doc:`_notebooks/d
 Image processing
 ----------------
 Further processing of the reconstructed data such as quantitative parameter estimation is available.
-Our examples contain a notebooks showing how to read in DICOM images and perform qMRI paramter estimation using
+Our examples contain a notebook showing how to read in DICOM images and perform qMRI parameter estimation using
 a non-linear optimizer: :doc:`_notebooks/qmri_sg_challenge_2024_t1`,