Nianchao-Code
commented
1 year ago Hi nickeener! Thank you for reaching out and trying our cell segmentation evaluation method. I appreciate your interest and the valuable question you have raised. I apologize for any confusion caused by the differences in the output you obtained compared to the results I presented in my paper.
After carefully reviewing your comment and testing, I have identified the problem you mentioned. It is likely due to an oversight on my part during the explanation of the evaluation method in my code. I apologize for any confusion caused by this oversight.
To clarify, here is the intended structure of the results:
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Test Result: This row should consist of four integer values representing different intensity levels used for hand segmentation of the original images.
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Accuracy Rates (Conventional Evaluation): This row should contain four accuracy measures: Dice score, Precision, Recall, and F-measure values. These measures are used to compare the performance of our POSEA algorithm against conventional evaluation methods.
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Accuracy Rates (POSEA): This row should display four accuracy measures generated for the entire image using our POSEA algorithm.
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Additional Pandas Dataframe: The dataframe you mentioned contains F-measure, Precision, and Recall values, representing the accuracy rates calculated for each individual cell in your hand segmentation image. These values provide insights into the accuracy of segmentation for each cell.
Once again, I apologize for any confusion caused by the lack of clarity in my code comments. I have taken note of your feedback and will make sure to improve the documentation and explanation of the evaluation method to avoid such confusion in the future.
If you have any further questions or need additional clarification, please don't hesitate to let me know. I'm more than happy to assist you in any way I can.
Thank you for your understanding, and I appreciate your interest in our work.
Hi, thanks for creating this interesting new way of evaluating cell segmentation results, though your documentation does leave a lot to be desired (unless it is located elsewhere that I'm unaware of). It's not too difficult to figure out how to run on my data (just need to replace the input file names) but I'm not sure how to interpret the output. It's a pandas dataframe with F-measure, Precision, and Recall as columns and then 4 different rows. The column identities are obvious but it's not clear to me what each row represents, could you explain this? Thanks!