LeukoSegmenter: A Double Encoder-decoder Based Network for Leukocyte Segmentation From Blood Smear Images Article Swipe
Sabrina Dhalla
,
Ajay Mittal
,
Savita Gupta
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-997876/v1
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-997876/v1
Segmentation of blood cells is a prerequisite step in automated morphological analysis of blood smear images, cell count determination and diagnosis of various diseases such as leukemia. It is extremely challenging due to different sizes, shapes, morphological characteristics and overlapping of blood cells. Due to its complicated nature, it is generally performed as a sequence of steps. However, sequential segmentation results in restricted accuracy due to cascading of errors that creep during each stage. On the contrary, pixel-wise segmentation of blood cells is a single step task and gives promising results. In this paper, we propose LeukoSegmenter, a double encoder-decoder for precise pixel-wise segmentation of leukocytes from blood smear images. It uses pre-trained ResNet18 based encoders and U-Net based decoders. Feature maps obtained from the first network are utilised as attention maps. These are used as input in conjunction with the original 3-channel image to obtain final mask from the second network. This mechanism allows the latter encoder-decoder pair to focus explicitly on leukocytes and ignore other blood cells and debris, thus improving the segmentation accuracy. Experiments on ALL-IDB1 dataset show that the proposed LeukoSegmenter achieves intersection-over-union score of 94.6827% and Dice score of 97.1987% which is superior than that of state-of-the-art methods.
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- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-997876/v1
- https://www.researchsquare.com/article/rs-997876/latest.pdf
- OA Status
- gold
- Cited By
- 1
- References
- 43
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3210159816
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- OpenAlex ID
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https://openalex.org/W3210159816Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.21203/rs.3.rs-997876/v1Digital Object Identifier
- Title
-
LeukoSegmenter: A Double Encoder-decoder Based Network for Leukocyte Segmentation From Blood Smear ImagesWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
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2021-10-26Full publication date if available
- Authors
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Sabrina Dhalla, Ajay Mittal, Savita GuptaList of authors in order
- Landing page
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https://doi.org/10.21203/rs.3.rs-997876/v1Publisher landing page
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https://www.researchsquare.com/article/rs-997876/latest.pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.researchsquare.com/article/rs-997876/latest.pdfDirect OA link when available
- Concepts
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Encoder, Computer science, Segmentation, Artificial intelligence, Computer vision, Pattern recognition (psychology), Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
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2022: 1Per-year citation counts (last 5 years)
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43Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.LeukoSegmenter | 185 |
| abstract_inverted_index.LeukoSegmenter, | 97 |
| abstract_inverted_index.characteristics | 38 |
| abstract_inverted_index.encoder-decoder | 100, 158 |
| abstract_inverted_index.state-of-the-art | 202 |
| abstract_inverted_index.<title>Abstract</title> | 0 |
| abstract_inverted_index.intersection-over-union | 187 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5026724995 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| corresponding_institution_ids | https://openalex.org/I51452335 |
| citation_normalized_percentile.value | 0.42406364 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |