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A Novel Technique for Segmenting Platelets by k-Means Clustering

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Advances in Computing and Data Sciences (ICACDS 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 721))

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Abstract

Platelet is a major component of various blood cells present in blood that helps in clotting of blood. Platelet count often becomes a crucial diagnostic parameter to identify several diseases like dengue, yellow fever, etc. The traditional process of counting platelets by examining blood slides under a conventional optical microscope is subjected to human errors due to manual inspection. In addition, the overhead on pathologist increases manifold when huge numbers of blood samples are to be tested. In this work, we have developed an Android-based mobile app, which takes as input the microscopic image of blood smear and gives as output the total platelet count present in the image. This system reduces the dependency on expert pathologists and avoids manual errors. A comparative study between platelet counts obtained from expert lab technicians and the one given by our developed app have shown it to be robust and efficient for automated platelet counting.

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Acknowledgement

Authors are thankful to Department of Bio-Technology, Govt. of India (Letter No. - Letter No -BT/PR8456/MED/29/739/2013) for their support.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Jadavpur University, Kolkata, 700032, India

    Kaushiki Roy, Ratnadeep Dey, Debotosh Bhattacharjee & Mita Nasipuri

  2. Department of Computer Science and Engineering, RCC Institute of Information Technology, Kolkata, 700015, India

    Pramit Ghosh

Authors
  1. Kaushiki Roy
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  2. Ratnadeep Dey
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  3. Debotosh Bhattacharjee
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  4. Mita Nasipuri
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  5. Pramit Ghosh
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Corresponding author

Correspondence to Kaushiki Roy .

Editor information

Editors and Affiliations

  1. Krishna Engineering College, Ghaziabad, Uttar Pradesh, India

    Mayank Singh

  2. Jaypee University of Information Technology, Waknaghat, Himachal Pradesh, India

    P.K. Gupta

  3. Department of Computer Science and Engineering, Raghogarh, Jaypee University of Engineering and Technology, Guna, Madhya Pradesh, India

    Vipin Tyagi

  4. Indira Gandhi Delhi Technical University, New Delhi, India

    Arun Sharma

  5. School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Ontario, Canada

    Tuncer Ören

  6. Department of Computer and Information Science, University of Michigan-Dearborn, Dearborn, Michigan, USA

    William Grosky

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Roy, K., Dey, R., Bhattacharjee, D., Nasipuri, M., Ghosh, P. (2017). A Novel Technique for Segmenting Platelets by k-Means Clustering. In: Singh, M., Gupta, P., Tyagi, V., Sharma, A., Ören, T., Grosky, W. (eds) Advances in Computing and Data Sciences. ICACDS 2016. Communications in Computer and Information Science, vol 721. Springer, Singapore. https://doi.org/10.1007/978-981-10-5427-3_3

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  • DOI: https://doi.org/10.1007/978-981-10-5427-3_3

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-5426-6

  • Online ISBN: 978-981-10-5427-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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