auto updates (#399)

Signed-off-by: monai-bot <monai.miccai2019@gmail.com>

Signed-off-by: monai-bot <monai.miccai2019@gmail.com>
Co-authored-by: Mingxin Zheng <18563433+mingxin-zheng@users.noreply.github.com>

Author: monai-bot

prostate-mri-lesion-seg/LICENSE

@@ -1,54 +1,54 @@
-Prostate-MRI_Lesion_Detection, v3.0 (Release date: September 17, 2024)
-DEFINITIONS: AUTHOR(S) NVIDIA Corp. and National Cancer Institute, NIH
-
-PROVIDER: the National Cancer Institute (NCI), a participating institute of the
-National Institutes of Health (NIH), and an agency of the United States Government.
-
-SOFTWARE: the machine readable, binary, object code form,
-and the related documentation for the modules of the Prostate-MRI_Lesion_Detection, v2.0
-software package, which is a collection of operators which accept (T2, ADC, and High
-b-value DICOM images) and produce prostate organ and lesion segmentation files
-
-RECIPIENT: the party that downloads the software.
-
-By downloading or otherwise receiving the SOFTWARE, RECIPIENT may
-use and/or redistribute the SOFTWARE, with or without modification,
-subject to RECIPIENT’s agreement to the following terms:
-
-1. THE SOFTWARE SHALL NOT BE USED IN THE TREATMENT OR DIAGNOSIS
-OF HUMAN SUBJECTS.  RECIPIENT is responsible for
-compliance with all laws and regulations applicable to the use
-of the SOFTWARE.
-
-2. THE SOFTWARE is distributed for NON-COMMERCIAL RESEARCH PURPOSES ONLY. RECIPIENT is
-responsible for appropriate-use compliance.
-
-3.	RECIPIENT agrees to acknowledge PROVIDER’s contribution and
-the name of the author of the SOFTWARE in all written publications
-containing any data or information regarding or resulting from use
-of the SOFTWARE.
-
-4.	THE SOFTWARE IS PROVIDED "AS IS" AND ANY EXPRESS OR IMPLIED
-WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
-OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT
-ARE DISCLAIMED. IN NO EVENT SHALL THE PROVIDER OR THE INDIVIDUAL DEVELOPERS
-BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
-CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
-SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
-INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
-CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
-ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
-THE POSSIBILITY OF SUCH DAMAGE.
-
-5.	RECIPIENT agrees not to use any trademarks, service marks, trade names,
-logos or product names of NVIDIA, NCI or NIH to endorse or promote products derived
-from the SOFTWARE without specific, prior and written permission.
-
-6.	For sake of clarity, and not by way of limitation, RECIPIENT may add its
-own copyright statement to its modifications or derivative works of the SOFTWARE
-and may provide additional or different license terms and conditions in its
-sublicenses of modifications or derivative works of the SOFTWARE provided that
-RECIPIENT’s use, reproduction, and distribution of the SOFTWARE otherwise complies
-with the conditions stated in this Agreement. Whenever Recipient distributes or
-redistributes the SOFTWARE, a copy of this Agreement must be included with
-each copy of the SOFTWARE.
+Prostate-MRI_Lesion_Detection, v3.0 (Release date: September 17, 2024)
+DEFINITIONS: AUTHOR(S) NVIDIA Corp. and National Cancer Institute, NIH
+
+PROVIDER: the National Cancer Institute (NCI), a participating institute of the
+National Institutes of Health (NIH), and an agency of the United States Government.
+
+SOFTWARE: the machine readable, binary, object code form,
+and the related documentation for the modules of the Prostate-MRI_Lesion_Detection, v2.0
+software package, which is a collection of operators which accept (T2, ADC, and High
+b-value DICOM images) and produce prostate organ and lesion segmentation files
+
+RECIPIENT: the party that downloads the software.
+
+By downloading or otherwise receiving the SOFTWARE, RECIPIENT may
+use and/or redistribute the SOFTWARE, with or without modification,
+subject to RECIPIENT’s agreement to the following terms:
+
+1. THE SOFTWARE SHALL NOT BE USED IN THE TREATMENT OR DIAGNOSIS
+OF HUMAN SUBJECTS.  RECIPIENT is responsible for
+compliance with all laws and regulations applicable to the use
+of the SOFTWARE.
+
+2. THE SOFTWARE is distributed for NON-COMMERCIAL RESEARCH PURPOSES ONLY. RECIPIENT is
+responsible for appropriate-use compliance.
+
+3.	RECIPIENT agrees to acknowledge PROVIDER’s contribution and
+the name of the author of the SOFTWARE in all written publications
+containing any data or information regarding or resulting from use
+of the SOFTWARE.
+
+4.	THE SOFTWARE IS PROVIDED "AS IS" AND ANY EXPRESS OR IMPLIED
+WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
+OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT
+ARE DISCLAIMED. IN NO EVENT SHALL THE PROVIDER OR THE INDIVIDUAL DEVELOPERS
+BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
+THE POSSIBILITY OF SUCH DAMAGE.
+
+5.	RECIPIENT agrees not to use any trademarks, service marks, trade names,
+logos or product names of NVIDIA, NCI or NIH to endorse or promote products derived
+from the SOFTWARE without specific, prior and written permission.
+
+6.	For sake of clarity, and not by way of limitation, RECIPIENT may add its
+own copyright statement to its modifications or derivative works of the SOFTWARE
+and may provide additional or different license terms and conditions in its
+sublicenses of modifications or derivative works of the SOFTWARE provided that
+RECIPIENT’s use, reproduction, and distribution of the SOFTWARE otherwise complies
+with the conditions stated in this Agreement. Whenever Recipient distributes or
+redistributes the SOFTWARE, a copy of this Agreement must be included with
+each copy of the SOFTWARE.

prostate-mri-lesion-seg/prostate_mri_lesion_seg_app/__main__.py

@@ -1,4 +1,4 @@
-'''
+"""
 Prostate-MRI_Lesion_Detection, v3.0 (Release date: September 17, 2024)
 DEFINITIONS: AUTHOR(S) NVIDIA Corp. and National Cancer Institute, NIH
 
@@ -52,7 +52,7 @@
 RECIPIENT’s use, reproduction, and distribution of the SOFTWARE otherwise complies
 with the conditions stated in this Agreement. Whenever Recipient distributes or
 redistributes the SOFTWARE, a copy of this Agreement must be included with
-each copy of the SOFTWARE.'''
+each copy of the SOFTWARE."""
 
 from app import AIProstateLesionSegApp
 

prostate-mri-lesion-seg/prostate_mri_lesion_seg_app/app.py

@@ -1,4 +1,4 @@
-'''
+"""
 Prostate-MRI_Lesion_Detection, v3.0 (Release date: September 17, 2024)
 DEFINITIONS: AUTHOR(S) NVIDIA Corp. and National Cancer Institute, NIH
 
@@ -52,24 +52,24 @@
 RECIPIENT’s use, reproduction, and distribution of the SOFTWARE otherwise complies
 with the conditions stated in this Agreement. Whenever Recipient distributes or
 redistributes the SOFTWARE, a copy of this Agreement must be included with
-each copy of the SOFTWARE.'''
+each copy of the SOFTWARE."""
 
 import logging
 from pathlib import Path
 
+from custom_lesion_classifier_operator import ProstateLesionClassifierOperator
+from custom_lesion_seg_operator import ProstateLesionSegOperator
+
+# Local imports
+from organ_seg_operator import ProstateSegOperator
+
 # MONAI Deploy SDK imports
 from monai.deploy.conditions import CountCondition
 from monai.deploy.core import AppContext, Application
 from monai.deploy.operators.dicom_data_loader_operator import DICOMDataLoaderOperator
 from monai.deploy.operators.dicom_series_selector_operator import DICOMSeriesSelectorOperator
 from monai.deploy.operators.dicom_series_to_volume_operator import DICOMSeriesToVolumeOperator
 
-# Local imports
-from organ_seg_operator import ProstateSegOperator
-from custom_lesion_seg_operator import ProstateLesionSegOperator
-from custom_lesion_classifier_operator import ProstateLesionClassifierOperator
-
-
 # Custom rules for T2, ADC, and HIGHB series selection in ProstateX
 Rules_T2 = """
 {
@@ -128,6 +128,7 @@
 }
 """
 
+
 class AIProstateLesionSegApp(Application):
     def __init__(self, *args, **kwargs):
         """Creates an application instance."""
@@ -166,18 +167,32 @@ def compose(self):
         series_to_vol_HIGHB_op = DICOMSeriesToVolumeOperator(self, name="series_to_vol_HIGHB")
 
         # AI operators
-        organ_seg_op = ProstateSegOperator(self, app_context=app_context, model_path=model_path/"organ", name="organ_seg_op")
-        lesion_seg_op = ProstateLesionSegOperator(self, app_context=app_context, model_path=model_path, name="lesion_seg_op")
-        lesion_classifier_op = ProstateLesionClassifierOperator(self, app_context=app_context, model_path=model_path, name="lesion_classifier_op")
+        organ_seg_op = ProstateSegOperator(
+            self, app_context=app_context, model_path=model_path / "organ", name="organ_seg_op"
+        )
+        lesion_seg_op = ProstateLesionSegOperator(
+            self, app_context=app_context, model_path=model_path, name="lesion_seg_op"
+        )
+        lesion_classifier_op = ProstateLesionClassifierOperator(
+            self, app_context=app_context, model_path=model_path, name="lesion_classifier_op"
+        )
 
         #################### Pipeline DAG ####################
         # Data ingestion
         self.add_flow(study_loader_op, series_selector_T2_op, {("dicom_study_list", "dicom_study_list")})
         self.add_flow(study_loader_op, series_selector_ADC_op, {("dicom_study_list", "dicom_study_list")})
         self.add_flow(study_loader_op, series_selector_HIGHB_op, {("dicom_study_list", "dicom_study_list")})
-        self.add_flow(series_selector_T2_op, series_to_vol_T2_op, {("study_selected_series_list", "study_selected_series_list")})
-        self.add_flow(series_selector_ADC_op, series_to_vol_ADC_op, {("study_selected_series_list", "study_selected_series_list")})
-        self.add_flow(series_selector_HIGHB_op, series_to_vol_HIGHB_op, {("study_selected_series_list", "study_selected_series_list")})
+        self.add_flow(
+            series_selector_T2_op, series_to_vol_T2_op, {("study_selected_series_list", "study_selected_series_list")}
+        )
+        self.add_flow(
+            series_selector_ADC_op, series_to_vol_ADC_op, {("study_selected_series_list", "study_selected_series_list")}
+        )
+        self.add_flow(
+            series_selector_HIGHB_op,
+            series_to_vol_HIGHB_op,
+            {("study_selected_series_list", "study_selected_series_list")},
+        )
 
         # Organ inference
         self.add_flow(series_to_vol_T2_op, organ_seg_op, {("image", "image")})
@@ -198,6 +213,7 @@ def compose(self):
         self._logger.debug(f"End {self.compose.__name__}")
         #################### Pipeline DAG ####################
 
+
 if __name__ == "__main__":
     # Creates the app and test it standalone.
     logging.info(f"Begin {__name__}")

prostate-mri-lesion-seg/prostate_mri_lesion_seg_app/common.py

@@ -1,4 +1,4 @@
-'''
+"""
 Prostate-MRI_Lesion_Detection, v3.0 (Release date: September 17, 2024)
 DEFINITIONS: AUTHOR(S) NVIDIA Corp. and National Cancer Institute, NIH
 
@@ -52,13 +52,16 @@
 RECIPIENT’s use, reproduction, and distribution of the SOFTWARE otherwise complies
 with the conditions stated in this Agreement. Whenever Recipient distributes or
 redistributes the SOFTWARE, a copy of this Agreement must be included with
-each copy of the SOFTWARE.'''
+each copy of the SOFTWARE."""
 
-import numpy as np
 import copy
+
+import numpy as np
 from skimage.measure import label
 
 ###############################################################################
+
+
 def bounding_box_3d(nda):
 
     r = np.any(nda, axis=(1, 2))
@@ -80,6 +83,7 @@ def bounding_box_3d(nda):
 
     return bbox
 
+
 def crop_pos_classification_multi_channel_3d(nda, nda_gt, crop_size):
     if nda_gt.ndim == 4:
         nda_ref = np.amax(nda_gt, axis=0)
@@ -104,12 +108,12 @@ def crop_pos_classification_multi_channel_3d(nda, nda_gt, crop_size):
 
         nda = nda[
             ...,
-            indices[0]:indices[0] + crop_size[0],
-            indices[1]:indices[1] + crop_size[1],
-            indices[2]:indices[2] + crop_size[2]
-            ]
+            indices[0] : indices[0] + crop_size[0],
+            indices[1] : indices[1] + crop_size[1],
+            indices[2] : indices[2] + crop_size[2],
+        ]
 
-        gt = np.unique(nda_gt[label_image==1])[0]
+        gt = np.unique(nda_gt[label_image == 1])[0]
     elif num_crop > 1:
         images = []
         labels = []
@@ -125,10 +129,10 @@ def crop_pos_classification_multi_channel_3d(nda, nda_gt, crop_size):
 
             nda_crop = nda[
                 ...,
-                indices[0]:indices[0] + crop_size[0],
-                indices[1]:indices[1] + crop_size[1],
-                indices[2]:indices[2] + crop_size[2]
-                ]
+                indices[0] : indices[0] + crop_size[0],
+                indices[1] : indices[1] + crop_size[1],
+                indices[2] : indices[2] + crop_size[2],
+            ]
 
             gt = np.unique(nda_gt[label_image == k + 1])[0]
 
@@ -140,6 +144,7 @@ def crop_pos_classification_multi_channel_3d(nda, nda_gt, crop_size):
 
     return nda, gt
 
+
 def standard_normalization_multi_channel(nda):
     for _i in range(nda.shape[0]):
         if np.amax(np.abs(nda[_i, ...])) < 1e-7: