title: Framework for morphometric classification of cells in imaging flow cytometry.
abstract: Imaging flow cytometry is an emerging technology that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy. It allows high-throughput imaging of cells with good spatial resolution, while they are in flow. This paper proposes a general framework for the processing/classification of cells imaged using imaging flow cytometer. Each cell is localized by finding an accurate cell contour. Then, features reflecting cell size, circularity and complexity are extracted for the classification using SVM. Unlike the conventional iterative, semi-automatic segmentation algorithms such as active contour, we propose a noniterative, fully automatic graph-based cell localization. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using custom fabricated cost-effective microfluidics-based imaging flow cytometer. The proposed system is a significant development in the direction of building a cost-effective cell analysis platform that would facilitate affordable mass screening camps looking cellular morphology for disease diagnosis.
authors.affiliation: Department of Earth and Space Sciences, Indian Institute of Space Science and Technology, Thiruvananthapuram, Kerala, India.
authors.forename: G
authors.initials: G
authors.lastname: Gopakumar
authors.affiliation: Department of Instrumentation and Applied Physics, Indian Institute of Science, Bangalore, India.
authors.forename: Veerendra Kalyan
authors.initials: VK
authors.lastname: Jagannadh
authors.affiliation: Department of Instrumentation and Applied Physics, Indian Institute of Science, Bangalore, India.
authors.forename: Sai Siva
authors.initials: SS
authors.lastname: Gorthi
authors.affiliation: Department of Earth and Space Sciences, Indian Institute of Space Science and Technology, Thiruvananthapuram, Kerala, India.
authors.forename: Gorthi R K Sai
authors.initials: GR
authors.lastname: Subrahmanyam
mesh_terms: D000465:Algorithms; D045744:Cell Line, Tumor; D005434:Flow Cytometry / Q000379:methods*; D018922:HL-60 Cells; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D020014:K562 Cells; D044085:Microfluidics / Q000379:methods*
keywords: Classification; imaging flow cytometry; leukaemia; morphology; segmentation; texture features