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ENHANCE-PET / MOOSE

MOOSE (Multi-organ objective segmentation) a data-centric AI solution that generates multilabel organ segmentations to facilitate systemic TB whole-person research.The pipeline is based on nn-UNet and has the capability to segment 120 unique tissue classes from a whole-body 18F-FDG PET/CT image.
https://enhance.pet
GNU General Public License v3.0
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Can you help mi solve this error.Thanks,I use window10 system. #76

Closed shifuxiao closed 10 months ago

shifuxiao commented 11 months ago

(moose-env) E:\data>moosez -d ./input -m clin_ct_organs_v2

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/ /|/ / // / // /\ \/ / / // // / // //__/__//_/ /__(_)___/ A part of the ENHANCE community. Join us at www.enhance.pet to build the future of PET imaging together.

� CITATION:

Shiyam Sundar LK, Yu J, Muzik O, et al. Fully-automated, semantic segmentation of whole-body 18F-FDG PET/CT images based on data-centric artificial intelligence. J Nucl Med. June 2022. Copyright 2022, Quantitative Imaging and Medical Physics Team, Medical University of Vienna

� NOTE:

Imaging: Clinical | Modality: CT | Tissue of interest: Organs | nnUNet version: v2 Required modalities: ['CT'] | No. of modalities: 1 | Required prefix for non-DICOM files: ['CT_'] Warning: Subjects which don't have the required modalities [check file prefix] will be skipped. CUDA not available on this device. Predictions will be run on CPU.

� MODEL DOWNLOAD:

A local instance of Dataset123_Organs has been detected.

� STANDARDIZING INPUT DATA TO NIFTI:

Processing subjects... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 0% -:--:-- Standardization complete. Number of moose compliant subjects: 0 out of 0

� PREDICT:

Traceback (most recent call last): File "D:\anaconda3\envs\moose-env\lib\runpy.py", line 197, in _run_module_as_main \ Initiating return _run_code(code, main_globals, None, File "D:\anaconda3\envs\moose-env\lib\runpy.py", line 87, in _run_code exec(code, run_globals) File "D:\anaconda3\envs\moose-env\Scripts\moosez.exe__main__.py", line 7, in File "C:\Users\DELL\AppData\Roaming\Python\Python39\site-packages\moosez\moosez.py", line 199, in main time_per_dataset = total_elapsed_time / len(moose_compliant_subjects) ZeroDivisionError: float division by zero

LalithShiyam commented 11 months ago

Hi @shifuxiao,

Would you be kind enough to let me know the moosez version you are using. My guess is that you are using 2.2.8? Any particular reason why? If you are really interested in the organs, I would suggest to use the latest version of moosez. The organ model is much more robust since the training data was larger.

Please upgrade using pip install --upgrade moosez!

Also the error you are seeing is basically because there are no moose compatible directory structure. Kindly have a look at the readme section!

Please send me a screenshot of your folder structure, so that I can help you figure out what went wrong.

Cheers, Lalith

LalithShiyam commented 10 months ago

Hi @shifuxiao, is this solved? Kindly update!

LalithShiyam commented 10 months ago

@shifuxiao I am closing this, assuming this issue has been solved.