[ENH, MRG] Add volume/tumor segmentation

.circleci/config.yml

@@ -42,7 +42,7 @@ jobs:
         - run:
             name: Get Python running
             command: |
-              pip install --upgrade PyQt6!=6.6.1 "PyQt6-Qt6!=6.6.1" sphinx-gallery pydata-sphinx-theme numpydoc scikit-learn nilearn mne-bids autoreject git+https://github.com/pyvista/pyvista@main memory_profiler sphinxcontrib.bibtex sphinxcontrib.youtube
+              pip install --upgrade PyQt6!=6.6.1 "PyQt6-Qt6!=6.6.1" sphinx-gallery pydata-sphinx-theme numpydoc scikit-learn nilearn mne-bids autoreject git+https://github.com/pyvista/pyvista@main memory_profiler sphinxcontrib.bibtex sphinxcontrib.youtube darkdetect qdarkstyle
               pip install -ve ./mne-python .
         - run:
             name: Check Qt
@@ -70,6 +70,7 @@ jobs:
             name: make html
             command: |
               make -C doc html
+            no_output_timeout: 30m
         - store_test_results:
             path: doc/_build/test-results
         - store_artifacts:

.gitignore

@@ -1,3 +1,5 @@
+tmp.*
+
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]

doc/conf.py

@@ -76,6 +76,7 @@
     # not documented
     "IntracranialElectrodeLocator",
     "VolSourceEstimateViewer",
+    "VolumeSegmenter",
 }
 numpydoc_validate = True
 numpydoc_validation_checks = {

mne_gui_addons/__init__.py

@@ -280,6 +280,54 @@ def itc(data):
     return gui
 
 
+@_verbose
+@_fill_doc
+def segment_volume(
+    base_image=None,
+    subject=None,
+    subjects_dir=None,
+    show=True,
+    block=False,
+    verbose=None,
+):
+    """Locate intracranial electrode contacts.
+
+    Parameters
+    ----------
+    base_image : path-like | nibabel.spatialimages.SpatialImage
+        The image on which to segment the volume. Defaults to the
+        freesurfer T1. Path-like inputs and nibabel image
+        objects are supported.
+    %(subject)s
+    %(subjects_dir)s
+    show : bool
+        Show the GUI if True.
+    block : bool
+        Whether to halt program execution until the figure is closed.
+    %(verbose)s
+
+    Returns
+    -------
+    gui : instance of VolumeSegmenter
+        The graphical user interface (GUI) window.
+    """
+    from mne.viz.backends._utils import _init_mne_qtapp, _qt_app_exec
+    from ._segment import VolumeSegmenter
+
+    app = _init_mne_qtapp()
+
+    gui = VolumeSegmenter(
+        base_image=base_image,
+        subject=subject,
+        subjects_dir=subjects_dir,
+        show=show,
+        verbose=verbose,
+    )
+    if block:
+        _qt_app_exec(app)
+    return gui
+
+
 class _GUIScraper(object):
     """Scrape GUI outputs."""
 
@@ -289,12 +337,20 @@ def __repr__(self):
     def __call__(self, block, block_vars, gallery_conf):
         from ._ieeg_locate import IntracranialElectrodeLocator
         from ._vol_stc import VolSourceEstimateViewer
+        from ._segment import VolumeSegmenter
         from sphinx_gallery.scrapers import figure_rst
         from qtpy import QtGui
 
         for gui in block_vars["example_globals"].values():
             if (
-                isinstance(gui, (IntracranialElectrodeLocator, VolSourceEstimateViewer))
+                isinstance(
+                    gui,
+                    (
+                        IntracranialElectrodeLocator,
+                        VolSourceEstimateViewer,
+                        VolumeSegmenter,
+                    ),
+                )
                 and not getattr(gui, "_scraped", False)
                 and gallery_conf["builder_name"] == "html"
             ):

mne_gui_addons/_core.py

@@ -27,6 +27,7 @@
 from matplotlib.backends.backend_qt5agg import FigureCanvas
 from matplotlib.figure import Figure
 from matplotlib.patches import Rectangle
+from matplotlib.colors import LinearSegmentedColormap
 
 from mne.viz.backends.renderer import _get_renderer
 from mne.viz.utils import safe_event
@@ -46,6 +47,48 @@
 _ZOOM_STEP_SIZE = 5
 _ZOOM_BORDER = 1 / 5
 
+# 20 colors generated to be evenly spaced in a cube, worked better than
+# matplotlib color cycle
+_UNIQUE_COLORS = [
+    (0.1, 0.42, 0.43),
+    (0.9, 0.34, 0.62),
+    (0.47, 0.51, 0.3),
+    (0.47, 0.55, 0.99),
+    (0.79, 0.68, 0.06),
+    (0.34, 0.74, 0.05),
+    (0.58, 0.87, 0.13),
+    (0.86, 0.98, 0.4),
+    (0.92, 0.91, 0.66),
+    (0.77, 0.38, 0.34),
+    (0.9, 0.37, 0.1),
+    (0.2, 0.62, 0.9),
+    (0.22, 0.65, 0.64),
+    (0.14, 0.94, 0.8),
+    (0.34, 0.31, 0.68),
+    (0.59, 0.28, 0.74),
+    (0.46, 0.19, 0.94),
+    (0.37, 0.93, 0.7),
+    (0.56, 0.86, 0.55),
+    (0.67, 0.69, 0.44),
+]
+_N_COLORS = len(_UNIQUE_COLORS)
+_CMAP = LinearSegmentedColormap.from_list("colors", _UNIQUE_COLORS, N=_N_COLORS)
+
+
+def _get_volume_info(img):
+    header = img.header
+    version = header["version"]
+    vol_info = dict(head=[20])
+    if version == 1:
+        version = f"{version}  # volume info valid"
+        vol_info["valid"] = version
+        vol_info["filename"] = img.get_filename()
+        vol_info["volume"] = header["dims"][:3]
+        vol_info["voxelsize"] = header["delta"]
+        vol_info["xras"], vol_info["yras"], vol_info["zras"] = header["Mdc"]
+        vol_info["cras"] = header["Pxyz_c"]
+    return vol_info
+
 
 @verbose
 def _load_image(img, verbose=None):
@@ -69,7 +112,13 @@ def _load_image(img, verbose=None):
     vox_mri_t = orig_mgh.header.get_vox2ras_tkr()
     aff_trans = nib.orientations.inv_ornt_aff(ornt_trans, img.shape)
     ras_vox_scan_ras_t = np.dot(vox_scan_ras_t, aff_trans)
-    return img_data, vox_mri_t, vox_scan_ras_t, ras_vox_scan_ras_t
+    return (
+        img_data,
+        vox_mri_t,
+        vox_scan_ras_t,
+        ras_vox_scan_ras_t,
+        _get_volume_info(orig_mgh),
+    )
 
 
 def _make_mpl_plot(
@@ -96,6 +145,12 @@ def _make_mpl_plot(
     return canvas, fig
 
 
+def make_label(name):
+    label = QLabel(name)
+    label.setAlignment(QtCore.Qt.AlignCenter)
+    return label
+
+
 class SliceBrowser(QMainWindow):
     """Navigate between slices of an MRI, CT, etc. image."""
 
@@ -106,7 +161,13 @@ class SliceBrowser(QMainWindow):
     )
 
     @_qt_safe_window(splash="_renderer.figure.splash", window="")
-    def __init__(self, base_image=None, subject=None, subjects_dir=None, verbose=None):
+    def __init__(
+        self,
+        base_image=None,
+        subject=None,
+        subjects_dir=None,
+        verbose=None,
+    ):
         """GUI for browsing slices of anatomical images."""
         # initialize QMainWindow class
         super(SliceBrowser, self).__init__()
@@ -175,6 +236,7 @@ def _load_image_data(self, base_image=None):
                 mr_vox_mri_t,
                 mr_vox_scan_ras_t,
                 mr_ras_vox_scan_ras_t,
+                self._mr_vol_info,
             ) = _load_image(op.join(self._subject_dir, "mri", f"{mri_img}.mgz"))
 
         # ready alternate base image if provided, otherwise use brain/T1
@@ -191,6 +253,7 @@ def _load_image_data(self, base_image=None):
                 self._vox_mri_t,
                 self._vox_scan_ras_t,
                 self._ras_vox_scan_ras_t,
+                self._vol_info,
             ) = _load_image(base_image)
             if self._mr_data is not None:
                 if self._mr_data.shape != self._base_data.shape or not np.allclose(
@@ -371,22 +434,24 @@ def _plot_images(self):
                 render=False,
             )
         if self._lh is not None and self._rh is not None and self._base_mr_aligned:
-            self._renderer.mesh(
+            self._lh_actor, _ = self._renderer.mesh(
                 *self._lh["rr"].T,
                 triangles=self._lh["tris"],
                 color="white",
                 opacity=0.2,
                 reset_camera=False,
                 render=False,
             )
-            self._renderer.mesh(
+            self._rh_actor, _ = self._renderer.mesh(
                 *self._rh["rr"].T,
                 triangles=self._rh["tris"],
                 color="white",
                 opacity=0.2,
                 reset_camera=False,
                 render=False,
             )
+        else:
+            self._lh_actor = self._rh_actor = None
         self._renderer.set_camera(
             azimuth=90, elevation=90, distance=300, focalpoint=tuple(self._ras)
         )
@@ -530,6 +595,7 @@ def _set_ras(self, ras, update_plots=True):
         logger.debug(f"Setting RAS: ({msg}) mm")
         if update_plots:
             self._move_cursors_to_pos()
+        self.setFocus()  # focus back to main
 
     def set_vox(self, vox):
         """Set the crosshairs to a given voxel coordinate.

mne_gui_addons/_ieeg_locate.py

@@ -25,9 +25,7 @@
     QComboBox,
 )
 
-from matplotlib.colors import LinearSegmentedColormap
-
-from ._core import SliceBrowser
+from ._core import SliceBrowser, _CMAP, _N_COLORS
 from mne.channels import make_dig_montage
 from mne.surface import _voxel_neighbors
 from mne.transforms import apply_trans, _get_trans, invert_transform
@@ -44,33 +42,6 @@
 _SEARCH_ANGLE_THRESH = np.deg2rad(30)
 _MISSING_PROP_OKAY = 0.25
 
-# 20 colors generated to be evenly spaced in a cube, worked better than
-# matplotlib color cycle
-_UNIQUE_COLORS = [
-    (0.1, 0.42, 0.43),
-    (0.9, 0.34, 0.62),
-    (0.47, 0.51, 0.3),
-    (0.47, 0.55, 0.99),
-    (0.79, 0.68, 0.06),
-    (0.34, 0.74, 0.05),
-    (0.58, 0.87, 0.13),
-    (0.86, 0.98, 0.4),
-    (0.92, 0.91, 0.66),
-    (0.77, 0.38, 0.34),
-    (0.9, 0.37, 0.1),
-    (0.2, 0.62, 0.9),
-    (0.22, 0.65, 0.64),
-    (0.14, 0.94, 0.8),
-    (0.34, 0.31, 0.68),
-    (0.59, 0.28, 0.74),
-    (0.46, 0.19, 0.94),
-    (0.37, 0.93, 0.7),
-    (0.56, 0.86, 0.55),
-    (0.67, 0.69, 0.44),
-]
-_N_COLORS = len(_UNIQUE_COLORS)
-_CMAP = LinearSegmentedColormap.from_list("ch_colors", _UNIQUE_COLORS, N=_N_COLORS)
-
 
 class ComboBox(QComboBox):
     """Dropdown menu that emits a click when popped up."""