**Major updates:**
* Archives are now converted case-by-case, instead of performing each phase after the other (i.e. collecting metadata for all cases, then converting images).
* Logging has improved and now offers three levels of verbosity: 1) show full case log when something goes wrong (default), 2) show full log for all cases, and 0) off.
* Improved usability of command-line interface: both DICOM → MHA and MHA → nnU-Net conversions are now available, as well as the generation of the conversion settings.
* Conversion of dynamic contrast-enhanced (DCE) scans is now supported (but experimental, feedback is welcome).
**Updates that may require you to update your existing scripts:**
* Some parameter names have changed (e.g. `input_path` to `input_dir` in `MHA2nnUNetConverter`). Please refer to the README or source code for the new values.
* Conversion settings for DICOM → MHA now require the `patient_id` and `study_id` for each item.
**Minor updates:**
* Multiprocessing is now optional. Set `num_threads=1` to turn off.
* Improved creation of dataset.json for nnUNet raw data archive.
* Any DICOM tag can now be used to match cases to their target MHA file.
* The way values from DICOM tags are matched with the provided values is now configurable. See Dicom2MHAConverter's docstring for details.
**Improved testing:**
* Test DICOM → MHA conversion from both Python and the command line interface
* Test conversion of DCE scans