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The authors have provided satisfactory comments to the reviewers' concerns. The article is accepted based on revisions.
[# PeerJ Staff Note - this decision was reviewed and approved by Jyotismita Chaki, a PeerJ Section Editor covering this Section #]
Good
Good
Good
The authors have addressed all my concerns.
The review fits well within the journal's scope. The focus is on blood cell image segmentation and classification, which has broad cross-disciplinary applications. The introduction, motivation, and target audience are clear from the manuscript.
A good coherent read with connectivity between paragraphs and subsections. The methodology is consistent and comprehensive, and the sources are cited correctly where required.
Yes.
Yes.
None
The authors should revise according to the reviewers' comments.
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The paper titled "Blood Cell Image Segmentation and Classification: A Systematic Review" aims to provide a comprehensive review of existing literature on blood cell image analysis using deep learning techniques, with a focus on segmentation and classification of white blood cells (WBC) and red blood cells (RBC). Overall, the provided sections of the paper demonstrate a well-structured and informative approach to the survey. The authors effectively communicate the importance of the topic, the motivation for their research, and the intended audience for their findings. The abstract provides a concise summary of the key aspects of the survey, while the introduction and motivation sections provide a more detailed background and rationale for the study. But before final submission, authors are required to consider the following comments:
Introduction and Research Questions: Your paper starts with a research question, which is a good approach. However, you might consider adding a more detailed introduction to provide context and motivation for your research questions. Explain why blood cell segmentation and classification are important and briefly discuss the challenges in this field.
Ethical Considerations: Given the increasing use of machine learning and AI in medical applications, it might be worthwhile to include a brief section on ethical considerations. Discuss potential ethical challenges related to automated diagnosis and patient data privacy.
References: Make sure to review and ensure the consistency of your references. Follow a specific citation style (e.g., APA, IEEE, etc.) consistently throughout the paper.
Proofreading: Carefully proofread the paper for any typographical or grammatical errors. A well-edited paper enhances its professionalism and readability.
Datasets and Benchmarks: Provide more details about the datasets and benchmarks used for testing these methods. Mention the size of the datasets, their sources, and any preprocessing steps applied. This will help readers understand the context in which these methods were evaluated.
This survey paper offers a comprehensive overview of the current research on blood image analysis using deep learning techniques. It addresses various aspects of the field, from segmentation to classification, and highlights the importance of considering multiple components in the diagnostic process. The review is within the scoope of the journal.
The language is clear but it requires a thorough proofread. The searched liturature provides an ample backgroud of the field.
It is required to discuss potential biases associated with researchers' choices in the methods section (add a new subsection). For example, why do many researchers choose manual data collection over predefined datasets?
Discussion on feature extraction of blood elements is vague. Elaborate more on this section, focusing on feature exraction of WBCs and RBCs. So that the reader can understand the importance of features selection separately of WBCs and RBCs
Tables 2, 4, 5, 6, 7 and Figures 3, 6, 7 require a detailed caption. Provide detalied description of all figures and tables.
None
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