Overlapping cell nuclei segmentation in microscopic images using deep belief networks
Abstract
This paper proposes a method for segmentation of nuclei of single/isolated and overlapping/touching immature white blood cells from microscopic images of B-Lineage acute lymphoblastic leukemia (ALL) prepared from peripheral blood and bone marrow aspirate. We propose deep belief network approach for the segmentation of these nuclei. Simulation results and comparison with some of the existing methods demonstrate the efficacy of the proposed method.
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The ISBI 2019 dataset used contains 10,661 cell images from 73 subjects, including 7,272 leukemic B-lymphoblast (cancer) cell images from 47 patients and 3,389 normal B-lymphoid precursor cell images from 26 healthy persons.
“The data set used to build the diagnostic model is the ISBI 2019 data set [16–20], and 10661 cell pictures of 73 subjects were selected, including 7272 pictures of leukemic B-lymphoblast cells (cancer cells) from 47 all patients and 3389 pictures of B-lymphoid precursors (normal cells) from 26 healthy persons.”
From Method for diagnosis of acute lymphoblastic leukemia based on vit-cnn ensemble model (2021) · cites this paper as [17]
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Method for diagnosis of acute lymphoblastic leukemia based on vit-cnn ensemble model
Jiang, Z., Dong, Z., Wang, L., & Jiang, W. (2021) · Computational Intelligence and Neuroscience · doi:10.1155/2021/7529893 · Cited by 124 · see citing works
An Aggregated-Based Deep Learning Method for Leukemic B-lymphoblast Classification
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- Authors
- Duggal, R., Gupta, A., Gupta, R., Wadhwa, M., & Ahuja, C.
- Affiliations
- Indraprastha Institute of Information Technology Delhi (IN)
- All India Institute of Medical Sciences (IN)
- Venue
- Proceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing
- Publisher
- ACM
- Published
- 2016-12-18
- Pages
- 1-8
- OpenAlex
- W2567699853
- Cited by
- 80
- References
- 16
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 7 · 2023: 4 · 2022: 13 · 2021: 15 · 2020: 8 · 2019: 23 · 2018: 3 · 2017: 1
- FWCI
- 3.12
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Indian Conference on Computer Vision, Graphics and Image Processing (publishedVersion)
- Funders
- Ministry of Communication and IT, Govt. of India (1(7)/2014-ME&HI)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Digital Imaging for Blood Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Keywords
- nuclei segmentation, overlapping nuclei, deep belief network, B-cell acute lymphoblastic leukemia, bone marrow aspirate, peripheral blood, microscopic images
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