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Building without rt_utils
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@dbouget
dbouget committed Aug 21, 2023
1 parent a27cfa0 commit 08cefb8
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Showing 6 changed files with 106 additions and 106 deletions.
2 changes: 1 addition & 1 deletion .github/workflows/build_macos.yml
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Expand Up @@ -2,7 +2,7 @@ name: Build macOS

on:
push:
branches: [master,update]
branches: [master]
pull_request:
branches:
- '*'
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2 changes: 1 addition & 1 deletion .github/workflows/build_windows.yml
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Expand Up @@ -2,7 +2,7 @@ name: Build Windows

on:
push:
branches: [master, update]
branches: [master]
pull_request:
branches:
- '*'
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4 changes: 2 additions & 2 deletions assets/main.spec
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Expand Up @@ -19,8 +19,8 @@ print("PLATFORM:", sys.platform)

# fix hidden imports
hidden_imports = loadtxt(cwd + "/assets/requirements.txt", comments="#", delimiter=",", unpack=False, dtype=str)
hidden_imports = [x.split("=")[0] for x in hidden_imports] + ["raidionicsrads", "raidionicsseg", "ants", "sklearn",
"scikit-learn", "statsmodels", "gevent", "distutils", "PySide6", "gdown", "pydicom", "rt_utils"]
hidden_imports = [x.split("=")[0] for x in hidden_imports] + [ants", "sklearn", "scikit-learn",
"statsmodels", "gevent", "distutils", "PySide6", "gdown", "raidionicsrads", "raidionicsseg"]
hidden_imports = [x.lower() for x in hidden_imports]

# copy dependencies and images, remove if folder already exists
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2 changes: 1 addition & 1 deletion assets/requirements.txt
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Expand Up @@ -2,4 +2,4 @@ gdown==4.7.1
names==0.3.0
PySide6==6.2.4
plotly==5.8.0
rt_utils==1.2.7
#rt_utils==1.2.7
200 changes: 100 additions & 100 deletions utils/data_structures/PatientParametersStructure.py
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Expand Up @@ -1103,103 +1103,103 @@ def get_all_reporting_uids_for_timestamp(self, timestamp_uid: str) -> List[str]:
res.append(im)
return res

def __convert_results_as_dicom_rtstruct(self) -> None:
"""
Exporting all annotations into a DICOM RTStruct.
"""
# @TODO. Preferences option to always dump the RTStruct additionally.
# Create one structure for each MRI, and save on disk only if not empty.

ts_uids = self.get_all_timestamps_uids()
for ts in ts_uids:
image_uids = self.get_all_mri_volumes_for_timestamp(timestamp_uid=ts)
for im_uid in image_uids:
image_object = self.get_mri_by_uid(mri_uid=im_uid)
linked_annotation_uids = self.get_all_annotations_for_mri(mri_volume_uid=im_uid)
existing_annotations = len(linked_annotation_uids) != 0
if existing_annotations:
# @TODO. Should the original DICOM files be used, or just convert on the fly with the existing
# DICOM tags, already stored in the Image structure?
existing_dicom = image_object.get_dicom_metadata() is not None
dicom_folderpath = os.path.join(os.path.dirname(image_object.get_usable_input_filepath()),
image_object.display_name, 'volume')
os.makedirs(dicom_folderpath, exist_ok=True)
original_image_sitk = sitk.ReadImage(image_object.get_usable_input_filepath())
direction = original_image_sitk.GetDirection()
writer = sitk.ImageFileWriter()
writer.KeepOriginalImageUIDOn()
modification_time = time.strftime("%H%M%S")
modification_date = time.strftime("%Y%m%d")

if not existing_dicom:
series_tag_values = [("0010|0020", self.unique_id), # Patient ID
("0008|0031", modification_time), # Series Time
("0008|0021", modification_date), # Series Date
("0008|0008", "DERIVED\\SECONDARY"), # Image Type
("0020|000e", "0000000." + modification_date + ".1" + modification_time), # Series Instance UID
("0020|0037", '\\'.join(map(str, (
direction[0], direction[3], direction[6], # Image Orientation (Patient)
direction[1], direction[4], direction[7])))),
("0008|103e", image_object.display_name + '-' + ts + '-' + image_object.get_sequence_type_str())] # Series Description
else:
# @TODO. Bug when using all the existing tags, not properly loadable in 3D Slicer...
original_series_tag_values = image_object.get_dicom_metadata()
# original_series_tag_values["0020|0037"] = '\\'.join(map(str, (
# direction[0], direction[3], direction[6], # Image Orientation (Patient)
# direction[1], direction[4], direction[7])))
# original_series_tag_values["0008|103e"] = "Created-Raidionics"
# original_series_tag_values["0008|0008"] = "DERIVED\\SECONDARY"
# original_series_tag_values["0008|0031"] = modification_time
# original_series_tag_values["0008|0021"] = modification_date
# original_series_tag_values = list(original_series_tag_values.items())
series_tag_values = [("0010|0020", original_series_tag_values['0010|0020']), # Patient ID
("0008|0031", modification_time), # Series Time
("0008|0021", modification_date), # Series Date
("0008|0008", "DERIVED\\SECONDARY"), # Image Type
("0020|000e", original_series_tag_values['0020|000e'] + modification_date + ".1" + modification_time), # Series Instance UID
("0020|0037", '\\'.join(map(str, (
direction[0], direction[3], direction[6], # Image Orientation (Patient)
direction[1], direction[4], direction[7])))),
("0008|103e", image_object.display_name + '-' + ts + '-' + image_object.get_sequence_type_str())] # Series Description

# Write slices to output directory
list(map(lambda i: dicom_write_slice(writer, series_tag_values, original_image_sitk, i,
dicom_folderpath), range(original_image_sitk.GetDepth())))

# @TODO. Should we check that it already exists on disk, to append to it, rather than building it from scratch?
rt_struct = rt_utils.RTStructBuilder.create_new(dicom_series_path=dicom_folderpath)
for anno_uid in linked_annotation_uids:
anno = self.get_annotation_by_uid(annotation_uid=anno_uid)
anno_sitk = sitk.ReadImage(anno.raw_input_filepath)
anno_roi = sitk.GetArrayFromImage(anno_sitk).transpose((1, 2, 0)).astype('bool')
rt_struct.add_roi(mask=anno_roi, color=anno.get_display_color()[0:3],
name=anno.get_annotation_class_str())
# # The atlas structures inclusion is slow, and heavy on disk, might not do it by default
# # @TODO. Maybe add specific export options to convert only upon specific user request.
# # @TODO. Might dump one RTStruct per atlas, to alleviate some weight
# linked_atlas_uids = self.get_all_atlases_for_mri(mri_volume_uid=im_uid)
# for atlas_uid in linked_atlas_uids:
# atlas = self.get_atlas_by_uid(atlas_uid=atlas_uid)
# atlas_sitk = sitk.ReadImage(atlas._raw_input_filepath)
# atlas_roi = sitk.GetArrayFromImage(atlas_sitk).transpose((1, 2, 0))
# atlas_description = atlas.get_class_description()
# for s in range(atlas_description.shape[0]):
# try:
# label_value = atlas_description.values[s][1]
# struct_name = atlas_description.values[s][2]
# struct_mask = deepcopy(atlas_roi)
# struct_mask[struct_mask != label_value] = 0
# struct_mask[struct_mask == label_value] = 1
# rt_struct.add_roi(mask=struct_mask.astype('bool'),
# color=atlas.get_class_display_color_by_index(s+1)[0:3],
# name=atlas.display_name + '_' + struct_name)
# except Exception:
# logging.warning("Failure to save {} atlas structure number {} as RTStruct.".format(atlas.display_name, s))

dest_rt_struct_filename = os.path.join(os.path.dirname(image_object.get_usable_input_filepath()),
image_object.display_name,
image_object.display_name + '_structures')
rt_struct.save(dest_rt_struct_filename)
else:
# Skipping radiological volumes without any annotation linked to.
pass
# def __convert_results_as_dicom_rtstruct(self) -> None:
# """
# Exporting all annotations into a DICOM RTStruct.
# """
# # @TODO. Preferences option to always dump the RTStruct additionally.
# # Create one structure for each MRI, and save on disk only if not empty.
#
# ts_uids = self.get_all_timestamps_uids()
# for ts in ts_uids:
# image_uids = self.get_all_mri_volumes_for_timestamp(timestamp_uid=ts)
# for im_uid in image_uids:
# image_object = self.get_mri_by_uid(mri_uid=im_uid)
# linked_annotation_uids = self.get_all_annotations_for_mri(mri_volume_uid=im_uid)
# existing_annotations = len(linked_annotation_uids) != 0
# if existing_annotations:
# # @TODO. Should the original DICOM files be used, or just convert on the fly with the existing
# # DICOM tags, already stored in the Image structure?
# existing_dicom = image_object.get_dicom_metadata() is not None
# dicom_folderpath = os.path.join(os.path.dirname(image_object.get_usable_input_filepath()),
# image_object.display_name, 'volume')
# os.makedirs(dicom_folderpath, exist_ok=True)
# original_image_sitk = sitk.ReadImage(image_object.get_usable_input_filepath())
# direction = original_image_sitk.GetDirection()
# writer = sitk.ImageFileWriter()
# writer.KeepOriginalImageUIDOn()
# modification_time = time.strftime("%H%M%S")
# modification_date = time.strftime("%Y%m%d")
#
# if not existing_dicom:
# series_tag_values = [("0010|0020", self.unique_id), # Patient ID
# ("0008|0031", modification_time), # Series Time
# ("0008|0021", modification_date), # Series Date
# ("0008|0008", "DERIVED\\SECONDARY"), # Image Type
# ("0020|000e", "0000000." + modification_date + ".1" + modification_time), # Series Instance UID
# ("0020|0037", '\\'.join(map(str, (
# direction[0], direction[3], direction[6], # Image Orientation (Patient)
# direction[1], direction[4], direction[7])))),
# ("0008|103e", image_object.display_name + '-' + ts + '-' + image_object.get_sequence_type_str())] # Series Description
# else:
# # @TODO. Bug when using all the existing tags, not properly loadable in 3D Slicer...
# original_series_tag_values = image_object.get_dicom_metadata()
# # original_series_tag_values["0020|0037"] = '\\'.join(map(str, (
# # direction[0], direction[3], direction[6], # Image Orientation (Patient)
# # direction[1], direction[4], direction[7])))
# # original_series_tag_values["0008|103e"] = "Created-Raidionics"
# # original_series_tag_values["0008|0008"] = "DERIVED\\SECONDARY"
# # original_series_tag_values["0008|0031"] = modification_time
# # original_series_tag_values["0008|0021"] = modification_date
# # original_series_tag_values = list(original_series_tag_values.items())
# series_tag_values = [("0010|0020", original_series_tag_values['0010|0020']), # Patient ID
# ("0008|0031", modification_time), # Series Time
# ("0008|0021", modification_date), # Series Date
# ("0008|0008", "DERIVED\\SECONDARY"), # Image Type
# ("0020|000e", original_series_tag_values['0020|000e'] + modification_date + ".1" + modification_time), # Series Instance UID
# ("0020|0037", '\\'.join(map(str, (
# direction[0], direction[3], direction[6], # Image Orientation (Patient)
# direction[1], direction[4], direction[7])))),
# ("0008|103e", image_object.display_name + '-' + ts + '-' + image_object.get_sequence_type_str())] # Series Description
#
# # Write slices to output directory
# list(map(lambda i: dicom_write_slice(writer, series_tag_values, original_image_sitk, i,
# dicom_folderpath), range(original_image_sitk.GetDepth())))
#
# # @TODO. Should we check that it already exists on disk, to append to it, rather than building it from scratch?
# rt_struct = rt_utils.RTStructBuilder.create_new(dicom_series_path=dicom_folderpath)
# for anno_uid in linked_annotation_uids:
# anno = self.get_annotation_by_uid(annotation_uid=anno_uid)
# anno_sitk = sitk.ReadImage(anno.raw_input_filepath)
# anno_roi = sitk.GetArrayFromImage(anno_sitk).transpose((1, 2, 0)).astype('bool')
# rt_struct.add_roi(mask=anno_roi, color=anno.get_display_color()[0:3],
# name=anno.get_annotation_class_str())
# # # The atlas structures inclusion is slow, and heavy on disk, might not do it by default
# # # @TODO. Maybe add specific export options to convert only upon specific user request.
# # # @TODO. Might dump one RTStruct per atlas, to alleviate some weight
# # linked_atlas_uids = self.get_all_atlases_for_mri(mri_volume_uid=im_uid)
# # for atlas_uid in linked_atlas_uids:
# # atlas = self.get_atlas_by_uid(atlas_uid=atlas_uid)
# # atlas_sitk = sitk.ReadImage(atlas._raw_input_filepath)
# # atlas_roi = sitk.GetArrayFromImage(atlas_sitk).transpose((1, 2, 0))
# # atlas_description = atlas.get_class_description()
# # for s in range(atlas_description.shape[0]):
# # try:
# # label_value = atlas_description.values[s][1]
# # struct_name = atlas_description.values[s][2]
# # struct_mask = deepcopy(atlas_roi)
# # struct_mask[struct_mask != label_value] = 0
# # struct_mask[struct_mask == label_value] = 1
# # rt_struct.add_roi(mask=struct_mask.astype('bool'),
# # color=atlas.get_class_display_color_by_index(s+1)[0:3],
# # name=atlas.display_name + '_' + struct_name)
# # except Exception:
# # logging.warning("Failure to save {} atlas structure number {} as RTStruct.".format(atlas.display_name, s))
#
# dest_rt_struct_filename = os.path.join(os.path.dirname(image_object.get_usable_input_filepath()),
# image_object.display_name,
# image_object.display_name + '_structures')
# rt_struct.save(dest_rt_struct_filename)
# else:
# # Skipping radiological volumes without any annotation linked to.
# pass
2 changes: 1 addition & 1 deletion utils/utilities.py
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Expand Up @@ -9,7 +9,7 @@
import os
import SimpleITK as sitk
import numpy as np
import rt_utils
# import rt_utils


def get_type_from_string(enum_type: Enum, string: str) -> Union[str, int]:
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