Automatic Cell Counting From Microchannel Images Mikrokanal Görüntülerinden Otomatik Hücre Sayimi

Date

2022-01-01

Author

Erturk, Izzet Fatih
Alper Demir, Mehmet
Akar Ve, Gozde
Külah, Haluk

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

170
views

0
downloads

Cell counting is used in many fields such as disease diagnosis in medicine, and there are manual and automatic methods developed for this purpose. Because manual methods are slow and error-prone, automated cell counting methods such as flow cytometry have been developed. Flow cytometry methods are based on analyzing cells one by one by passing the cell-containing fluid through a microchannel. These methods allow obtaining cell sizes in addition to automatic cell counting. In this study, an image processing and object tracking based method for automated cell counting and analysis is presented. This method is based on recording images with a camera as the cells are passed through the microchannel. Cell counting is done by automatic detection and tracking of cells over recorded images. Image processing methods such as filtering, background modeling, segmentation, opening and closing are used for the detection of cells, and Kalman filter and Hungarian assignment algorithm are used for tracking. Cell analysis includes the average velocity of cells in the microchannel, cell sizes, and classification of cells by K-medoids method. Experiment results showed that the proposed method counts cells accurately under appropriate experimental conditions and can make size-based classification for cells having different sizes, therefore it can be used as a direct or reference method in cell experiments.

Subject Keywords

cell counting, microchannel, object trekking

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85138672851&origin=inward
https://hdl.handle.net/11511/101409

DOI

https://doi.org/10.1109/siu55565.2022.9864830

Conference Name

30th Signal Processing and Communications Applications Conference, SIU 2022

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Automatic cell counting from microchannel images Ertürk, İzzet Fatih; Akar, Gözde; Külah, Haluk; Department of Electrical and Electronics Engineering (2022-2) Cell counting is an important method used in many fields such as disease diagnosis in medicine. For example, the number of white blood cells in the blood gives information that there is a disease in the body. There are manual and automatic methods developed for cell counting. Although manual methods take a lot of time and are prone to error, they are preferred in many areas because they are less expensive than other methods. However, automated cell counting methods such as flow cytometry have been developed...
Numerical modeling and experimental investigation of cell manipulation using acoustophoresis Karaman, Alara; Özer, Mehmet Bülent; Department of Mechanical Engineering (2022-8-24) Several diseases, such as sickle cell disease and cancer, can affect the properties of cells. Manipulation or separation of the altered cell is necessary to diagnose such diseases. Acoustophoresis, the migration of particles by using acoustic standing waves, is a promising technique for bio-particle manipulation. This thesis presents numerical modelling and experimental investigation of using acoustophoresis for cell manipulation purposes. First, the trajectories of the cells in an acoustophoretic chip are ...
A visual object tracking benchmark for cell motility in time-lapse imaging Demir, H. Seckin; Cetin, A. Enis; Atalay, Rengül (2019-09-01) Automatic tracking of cells is a widely studied problem in various biomedical applications. Although there are numerous approaches for the video object tracking task in different contexts, the performance of these methods depends on many factors regarding the specific application they are used for. This paper presents a comparative study that specifically targets cell tracking problem and compares performance behavior of the recent algorithms. We propose a framework for the performance evaluation of the tra...
Automatic segmentation of mitochondria in scanning electron microscopy images Güven, Mehmet Çağrı; Mumcuoğlu, Ünal Erkan; Department of Information Systems (2021-9-7) Many studies have shown that shape of mitochondria indicates the occurrence of diseases. Scanning Electron Microscopy (SEM) enables to obtain image of internal structures of the cell and mitochondria. Automatic segmentation of mitochondria contributes to the decision of diseases by specialists. There is limited study about automatic segmentation of mitochondria in Serial Block-Face Scanning Electron Microscopy (SFBSEM) images. SBFSEM imaging technique provides full automation, well registered images, less t...
An Extensible security infrastructure for the secondary use of electronic health records in clinical research Eryılmaz, Elif; Toroslu, İsmail Hakkı; Doğaç, Asuman; Department of Computer Engineering (2013) In order to facilitate clinical research studies re-using Electronic Health Records (EHR) has a great potential. Besides interoperability, safeguarding the security and privacy of the medical data in the context of secondary use for clinical research is one of the most important challenges in this respect. In order to ensure that the clinical information is shared among EHR systems and clinical research systems in an ethical and safe way, there needs to be standards-based and adaptable security and privacy ...

Citation Formats

I. F. Erturk, M. Alper Demir, G. Akar Ve, and H. Külah, “Automatic Cell Counting From Microchannel Images Mikrokanal Görüntülerinden Otomatik Hücre Sayimi,” presented at the 30th Signal Processing and Communications Applications Conference, SIU 2022, Safranbolu, Türkiye, 2022, Accessed: 00, 2023. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85138672851&origin=inward.