6 feature integrate feedback

README.md

@@ -28,21 +28,69 @@ from stroke_segmentor.inferer import Inferer
 
 inferer = Inferer()
 pred = inferer.infer(
-    dwi_path="path/to/dwi.nii.gz",
     adc_path="path/to/adc.nii.gz",
+    dwi_path="path/to/dwi.nii.gz",
     segmentation_path="seg.nii.gz", # optional. the numpy array is always returned for direct usage
 )
 ```
 
+## Logging
+By default our package is silent, although we do use logging under the hood.  
+If you want, you can enable it like this:
+```py
+from loguru import logger
+
+logger.enable("stroke_segmentor")
+```
+
+
 ## Citation
 
 > [!IMPORTANT]
-> `stroke_segmentor` is part of the [BrainLesion](https://github.com/BrainLesion) suite.  
-> Please cite it support the development!  
-> https://github.com/BrainLesion#-citing-brainlesion-suite
+> `stroke_segmentor` is based on [DeepISLES](https://github.com/ezequieldlrosa/DeepIsles) and offers its NVAUTO algorithm
+> as part of the [BrainLesion](https://github.com/BrainLesion) suite.  
+> Please cite all relevant manuscripts!  
+
+
+### DeepISLES
+> de la Rosa, Ezequiel, et al. "DeepISLES: a clinically validated ischemic stroke segmentation model from the ISLES'22 challenge." Nature Communications 16.1 (2025): 7357.
+```
+
+@article{de2025deepisles,
+  title={DeepISLES: a clinically validated ischemic stroke segmentation model from the ISLES'22 challenge},
+  author={de la Rosa, Ezequiel and Reyes, Mauricio and Liew, Sook-Lei and Hutton, Alexandre and Wiest, Roland and Kaesmacher, Johannes and Hanning, Uta and Hakim, Arsany and Zubal, Richard and Valenzuela, Waldo and others},
+  journal={Nature Communications},
+  volume={16},
+  number={1},
+  pages={7357},
+  year={2025},
+  publisher={Nature Publishing Group UK London}
+}
+```
+
+### BrainLesion Suite
+> Kofler, F., Rosier, M., Astaraki, M., Möller, H., Mekki, I. I., Buchner, J. A., ... & Menze, B. (2025). BrainLesion Suite: A Flexible and User-Friendly Framework for Modular Brain Lesion Image Analysis. arXiv preprint arXiv:2507.09036.
+```
+
+@article{kofler2025brainlesion,
+  title={BrainLesion Suite: A Flexible and User-Friendly Framework for Modular Brain Lesion Image Analysis},
+  author={Kofler, Florian and Rosier, Marcel and Astaraki, Mehdi and M{\"o}ller, Hendrik and Mekki, Ilhem Isra and Buchner, Josef A and Schmick, Anton and Pfiffer, Arianna and Oswald, Eva and Zimmer, Lucas and others},
+  journal={arXiv preprint arXiv:2507.09036},
+  year={2025}
+}
+```
+
+### NVAUTO Algorithm
+>Siddique, M. M. R., Yang, D., He, Y., Xu, D., & Myronenko, A. (2022). Automated ischemic stroke lesion segmentation from 3D MRI. arXiv preprint arXiv:2209.09546.
+```
+@article{siddique2022automated,
+  title={Automated ischemic stroke lesion segmentation from 3D MRI},
+  author={Siddique, Md Mahfuzur Rahman and Yang, Dong and He, Yufan and Xu, Daguang and Myronenko, Andriy},
+  journal={arXiv preprint arXiv:2209.09546},
+  year={2022}
+}
+```
 
- This project is based on [DeepISLES](https://github.com/ezequieldlrosa/DeepIsles) and offers its NVAUTO algorithm.
- Please cite the [original manuscript](https://github.com/ezequieldlrosa/DeepIsles?tab=readme-ov-file#citations).
 
 ## Contributing
 

stroke_segmentor/inferer.py

@@ -8,6 +8,7 @@
 from numpy.typing import NDArray
 
 from stroke_segmentor.model_handler import ModelHandler
+from stroke_segmentor.utils.citation_reminder import citation_reminder
 
 
 class Inferer:
@@ -57,6 +58,7 @@ def _save(
         Path(segmentation_path).parent.mkdir(parents=True, exist_ok=True)
         SimpleITK.WriteImage(output_image, str(segmentation_path))
 
+    @citation_reminder
     def infer(
         self,
         adc_path: Union[str, Path],

stroke_segmentor/utils/citation_reminder.py

@@ -0,0 +1,57 @@
+import os
+
+from rich.console import Console
+
+
+CITATION_OVERVIEW_URL = (
+    "https://github.com/BrainLesion/stroke_segmentor?tab=readme-ov-file#citation"
+)
+DEEP_ISLES_PAPER_URL = "https://pubmed.ncbi.nlm.nih.gov/40783484/"
+DEEP_ISLES_PAPER_TEXT = 'de la Rosa, Ezequiel, et al. "DeepISLES: a clinically validated ischemic stroke segmentation model from the ISLES\'22 challenge." Nature Communications 16.1 (2025): 7357.'
+
+NVAUTO_PAPER_URL = "https://arxiv.org/abs/2209.09546"
+NVAUTO_PAPER_TEST = "Siddique, M. M. R., Yang, D., He, Y., Xu, D., & Myronenko, A. (2022). Automated ischemic stroke lesion segmentation from 3D MRI. arXiv preprint arXiv:2209.09546."
+
+BRAINLES_PAPER_URL = "https://arxiv.org/abs/2507.09036"
+BRAINLES_PAPER_TEXT = "Kofler, F., Rosier, M., Astaraki, M., Möller, H., Mekki, I. I., Buchner, J. A., ... & Menze, B. (2025). BrainLesion Suite: A Flexible and User-Friendly Framework for Modular Brain Lesion Image Analysis. arXiv preprint arXiv:2507.09036."
+
+
+def citation_reminder(func):
+    """Decorator to remind users to cite stroke-segmentor."""
+
+    def wrapper(*args, **kwargs):
+        if (
+            os.environ.get("STROKE_SEGMENTOR_CITATION_REMINDER", "true").lower()
+            == "true"
+        ):
+            console = Console()
+            console.rule("Thank you for using [bold]stroke-segmentor[/bold]")
+            console.print(
+                "This is the NVAUTO algorithmic solution from the ISLES'22 challenge.",
+                justify="center",
+            )
+            console.print(
+                "If you are using this tool, please cite the following work:",
+                justify="center",
+            )
+            console.print(
+                f"[italic]{DEEP_ISLES_PAPER_TEXT}[/italic] ({DEEP_ISLES_PAPER_URL})",
+                justify="center",
+            )
+            console.print(
+                f"[italic]{BRAINLES_PAPER_TEXT}[/italic] ({BRAINLES_PAPER_URL})",
+                justify="center",
+            )
+            console.print(
+                f"[italic]{NVAUTO_PAPER_TEST}[/italic] ({NVAUTO_PAPER_URL})",
+                justify="center",
+            )
+            console.print(
+                f"This information along with bibtex entries can be found at {CITATION_OVERVIEW_URL}",
+                justify="center",
+            )
+            console.rule()
+            console.line()
+        return func(*args, **kwargs)
+
+    return wrapper

stroke_segmentor/zenodo.py

@@ -176,6 +176,7 @@ def _extract_archive(
 
         with zipfile.ZipFile(buffer) as z:
             z.extractall(folder)
+            logger.info(f"Extracted data to {folder}")
 
         for file in folder.iterdir():
             if file.is_file() and file.suffix == ".zip":