MLens: Advancing the Real-Time Detection, Identification, and Counting of Pathogenic Microparasites Through a Web Interface

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Dear Authors,

Thank you for submitting your work to the Pathogens-MDPI journal.

This approach introduces a new Webapp called MLens, which is that automatically detect parasites. The results indicate that machine learning has the potential to make microparasite detection more efficient and less reliant on manual work in parasitology. This work represents a significant advancement, opening new possibilities for the application of machine learning in parasitology and substantially accelerating parasite detection.

It is mentioned that this provided solution represents the first software developed to detect myxozoans in the conclusion "This  is the first software developed for the detection of myxozoans, which will hopefully serve  as a gateway to the field of parasitology associated with AI. " The method looks ok and solid. No further controls required to be considered.

Based on my review I can see that the evidence and arguments are presented and they addressed the main question of the research (please refer to conclusion). Moreover, The authors summarized the findings and connect their results with the main purpose of their provided solution. However, future development should be clarified.

The idea looks original however, it would be better to show the major difference between the suggested solution and the other relevant solutions.

Some enhancements need to be considered to make your work better.

1.      Introduction

-        I suggest expanding the introduction and adding new section (e.g. background or literature) and then transfer the discussed works in the introduction to the new section.

-        At the end of this section, I suggest you add a paragraph representing the article map, which briefly describes what each section will discuss.

3. Results and Discussion

- Figures 7, 8 and 9: the quality should be enhanced.

5. Conclusion

Future work should be added to this section.

References:

 Please revise the references and add some of the missing conferences’ locations, such as “

 

[53] Cai, H.; Shangguan, H.; Wang, L. PC-Yolo: Enhanced YOLOv5-based defect detection system with improved partial convolution for ham sausage inspection. In Fourth International Conference on Computer Vision and Pattern Analysis (ICCPA 2024); SPIE, 2024, pp. 451-459. doi: https://doi.org/10.1117/12.3037840.”

 

Thank you

Author Response

Comment 1: Introduction

I suggest expanding the introduction and adding a new section (e.g., background or literature) and then transferring the discussed works in the introduction to the new section.
At the end of this section, I suggest you add a paragraph representing the article map, which briefly describes what each section will discuss.
Response 1:
We agree with this comment. A new section titled "Background" was created, and one of the discussed works in the introduction was transferred to this section to improve the organization and flow. Additionally, a paragraph outlining the article structure was added at the end of the introduction, summarizing the content of each section.

Comment 2: Results and Discussion

Figures 7, 8, and 9: The quality should be enhanced.
Response 2:
We agree with this comment. Higher-quality versions of Figures 7, 8, and 9 have been included in the revised manuscript to improve clarity and readability.

Comment 3: Conclusion

Future work should be added to this section.
Response 3:
We agree with this comment. A discussion of potential future work has been added, focusing on expanding the methodology to other domains and exploring advanced deep learning approaches for enhanced performance.

Comment 4: References

Please revise the references and add some of the missing conferences’ locations, such as:
“[53] Cai, H.; Shangguan, H.; Wang, L. PC-Yolo: Enhanced YOLOv5-based defect detection system with improved partial convolution for ham sausage inspection. In Fourth International Conference on Computer Vision and Pattern Analysis (ICCPA 2024); SPIE, 2024, pp. 451-459. doi: https://doi.org/10.1117/12.3037840.”

Response 4:
We revised the references and included missing details, such as conference locations, where necessary. For instance, the missing information in reference [53] has been added as follows:

"53.    Cai, H.; Shangguan, H.; Wang, L. PC-Yolo: Enhanced YOLOv5-based defect detection system with improved partial convo-lution for ham sausage inspection. In Fourth International Conference on Computer Vision and Pattern Analysis (ICCPA 2024); SPIE, 2024, pp. 451-459. Conference location: Anshan, China.doi: https://doi.org/10.1117/12.3037840"

Thank you for your valuable comments and suggestions. The changes addressing each point can be verified in the attached revised manuscript.

 

Reviewer 2 Report

Comments and Suggestions for Authors

The authors built a myxozoans images dataset and presented a pathogenic microparasites detection webapp, i.e. MLens. The data set they built may be very useful to the communities.  The paper is organized well and is written clearly.

minor comments:

1.  More about the background and motivation of the work should be added into the introduction section.

2.can Are there sub-figures, a-b, in Fig.3?  or maybe, you inserted a wrong figure.

3. The formulas mentioned in Line 215 are missing.

Author Response

Comment 1:
More about the background and motivation of the work should be added into the introduction section.

Response 1:
We agree with this comment. A new section dedicated to the background and motivation of the work has been added to provide additional context and clarity.

Comment 2:
Are there sub-figures, a-b, in Fig. 3? Or maybe, you inserted a wrong figure.

Response 2:
We confirm that the figure is correct. However, the caption previously contained an error, which has now been corrected.

Comment 3:
The formulas mentioned in Line 215 are missing.

Response 3:
Unfortunately, we were unable to identify the specific formulas referred to in this comment. We remain available for clarification or to make further adjustments as needed.

Thank you for your thoughtful comments. The changes addressing each point can be verified in the attached revised manuscript.