v0.3.2 release

README.md

@@ -35,6 +35,17 @@ The major features of this module are as follows.
     - the python API also providing data handler object through either nibabel and simpleITK to make convenient to the researcher can implement their own code.  
 
 
+### Update notes:
+##### BrkRaw v0.3.2
+
+1. Improved BIDS converter. 
+    - Bruker FieldMap will be accommodated into the BIDS excel sheets. With new feature, bids_converter separates fieldmap and magnitude image.  
+    - Multi-echo sequenced data will be converted as separate format.
+2. Bug patches.
+    - GUI visualization or crash issues related to certain conditions are patched.
+    - Matrix size instability has been patched, except multi-echo, all data will be converted to 3D + frame
+    - DTI slope correction issue is patched.
+
 ![example_alignment](imgs/brkraw_alignment.png)
 **Fig1.** Example subject alignment shown on FSLeyes, the overlayed localizer image for each slice axis(gray) and a EPI image(red) are align in the same space while the preserve subject orientation (correct R-L, I-S, A-P on rodent)
 
@@ -71,21 +82,20 @@ $ pip install bruker
 $ pip install git+https://github.com/dvm-shlee/bruker
 ```
 
-#### Conversion test result using [Bruker2Nifti_QA](https://gitlab.com/naveau/bruker2nifti_qa)
+#### Conversion reliability
 ![Robust Orientation](imgs/Bruker2Nifti_QA_challenge.png)
-**Overlapped images of all converted datasets of Bruker2Nifti_QA. Both within-session and between-session 
-are showing correct orientation. This image 
-represents that the orientation information is well-preserved in this tool. (from BrkRaw >= 0.3.2)**
+**We've tested our converter using the sample dataset from [Bruker2Nifti_QA](https://gitlab.com/naveau/bruker2nifti_qa) 
+and the results showed correct geometry and orientation for all datasets.** 
+- We are still looking for more datasets showing orientation issue, if you have any shareable dataset, please contact
+author. 
 
 #### Known issues
-- the last released version 0.3.1 does not convert DTI image correctly, please use 0.3.2 via github installation method.
-- The module have been tested for PV 5 to PV 6.0.1 datasets. but it may have issue with higher version.
-- The GUI may not work if the python does not be built with tkinter, please check above instruction.
-- If GUI popped up but not working after selecting the dir, make sure you entered to dataset dir.
-- If GUI cannot load zipped file, please check our example file located at 'examples' folder.
-- If you experience any other issue, please use 'issue' tab in Github to report.
-- The issues with lower priority.
-    - The GUI preview will show the image as matrix view not subject view and Magnitude dataset only.
+- The converter has not been tested the Paravision 360
+- Most of the GUI issues could be related to tkinter, please follow the above instruction first before open a issue.
+- Few update committed since the first stable version release, if you have any issue, please try the latest version.
+- For other unexpected issues, please use the issue channel.
+- There will be potential bug that occurred with new version updated, please let developer knows those issue by openning
+issue channel. Thank you for your contribution!
 
 ## Usage
 ### Command-line tool (brkraw)
@@ -214,12 +224,11 @@ $ brk-backup clean <rawdata path> <backup path>
 in the example directory.
 
 ### Contributing
-- Please contact shlee@unc.edu if you interest to contribute for following items.
-1. Share the dataset that showing any issues or incorrect orientation with this module.
-2. integration of reconstruction tool with Python API (such as BART tool).
-3. develop online analysis tools for fMRI or DTI study.
-4. Documentation or develop tutorials for various use.
-- Also if you experience any bug or have any suggestion to improve this tool, please let us know.
+- Please contact shlee@unc.edu if you interest to contributing in this project any direction.
+1. Improve BIDS organization
+2. Develop documentation or tutorials for below items using our Python API.
+    - FieldMap correction, reconstruction (integrate BART tool), acute quality control, fMRI and DTI analysis 
+- **if you experience any bug or have any suggestion to improve this tool, please let us know.**
 
 ### Credits and roles:
 #### Authors

brkraw/__init__.py

@@ -1,6 +1,6 @@
 from .lib import *
 
-__version__ = '0.3.2rc1'
+__version__ = '0.3.2'
 __all__ = ['BrukerLoader', '__version__']
 
 

brkraw/lib/loader.py

@@ -303,8 +303,10 @@ def get_niftiobj(self, scan_id, reco_id, crop=None, slope=False):
                         niiobj_ = Nifti1Image(imgobj_[..., crop[0]:], affine)
                     else:
                         niiobj_ = Nifti1Image(imgobj_[..., crop[0]:crop[1]], affine)
-                    niiobj_ = self._set_nifti_header(niiobj_, visu_pars, method, slope=slope)
-                    parser.append(niiobj_)
+                else:
+                    niiobj_ = Nifti1Image(imgobj_, affine)
+                niiobj_ = self._set_nifti_header(niiobj_, visu_pars, method, slope=slope)
+                parser.append(niiobj_)
             return parser
         else:
             if len(imgobj.shape) > 4:

brkraw/ui/previewer.py

@@ -82,7 +82,8 @@ def _load_image(self, brkraw_obj, scan_id, reco_id):
             f = multiply_all(dataobj.shape[3:])
             # all converted nifti must be 4D
             self._dataobj = dataobj.reshape([x, y, z, f])[:,:,::-1, ...]
-        self._dataobj = dataobj
+        else:
+            self._dataobj = dataobj
 
         # shape = brkraw_obj._get_matrix_size(visu_pars, dataobj)
         # self._dataobj = dataobj.reshape(shape[::-1]).T[:,:,::-1, ...]

brkraw/ui/scan_info.py

@@ -56,7 +56,10 @@ def load_data(self, brkraw_obj, scan_id, reco_id):
         self.textbox.insert(tk.END, 'RepetitionTime:\n - {} msec\n'.format(tr))
         self.textbox.insert(tk.END, 'EchoTime:\n - {} msec\n'.format(te))
         self.textbox.insert(tk.END, 'FlipAngle:\n - {} degree\n\n'.format(flip_angle))
-        self.textbox.insert(tk.END, 'PixelBandwidth:\n - {0:.3f} Hz\n'.format(pixel_bw))
+        if isinstance(pixel_bw, float):
+            self.textbox.insert(tk.END, 'PixelBandwidth:\n - {0:.3f} Hz\n'.format(pixel_bw))
+        else:
+            self.textbox.insert(tk.END, 'PixelBandwidth:\n - {} Hz\n'.format(pixel_bw))
         self.textbox.insert(tk.END, 'Dimension:\n - {}D\n'.format(dim))
         self.textbox.insert(tk.END, 'Matrix size:\n - {}\n'.format(size))
         self.textbox.insert(tk.END, 'Number of SlicePacks:\n - {}\n'.format(n_slicepacks))