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Passive Auto Focusing of Pathological Microscope with Intelligent Field Image Collection Mechanism

  • Image & Signal Processing
  • Published:
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Abstract

The microscope is one of the widely used pathological equipment to analyze body fluids like blood, sputum, etc. in granular level. In order to reduce workload on pathologists and strengthen the telehealth services, an automatic self-focusing microscope with different field image collection mechanism is required. In this work, the conversion of a compound microscope into a complete digital self-focusing automatic microscope, with intelligent field image collection mechanism, is discussed. This method uses passive autofocusing technique. In this method, most informative regions are identified on the basis of texture information. Features from these identified regions are used for autofocusing the microscope. This system is capable of collecting multiple snaps from different regions of the smear sample slides. The problem with the smear slide is that it has un-uniform thickness upon the glass slide. So some region has a very thick layer and some region has a very thin layer. In general, both of these regions are not considered for pathological analysis. The proposed system is capable to detect the region of smear slide which is suitable for collection of snap images. A soft computing approach is used to detect the desired regions of the sample in the slide. The Raspberry pi is used to design the control section. Multi-threaded parallel programming is used to optimize I/O execution and waiting time. The performance of the proposed system is satisfactory. The average peak signal-to-noise ratio (PSNR) is about 33 in comparison with manual focusing by the domain expert. The performance of the system in terms of computation time, which is calculated on the benchmark microscopic image dataset, is better than other learning-based methods. Autofocusing of pathological microscope with an intelligent field image collection mechanism is highly useful in the remote healthcare domain. This work basically describes a mechanism to migrate the conventional compound microscope into a tale-health service compatible (IoT enabled) microscope. This system is highly suitable for developing countries where an overall change of existing infrastructure is difficult due to economic reasons.

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Acknowledgements

Authors are thankful to Dr. Soumendu Datta (Medical practitioner) and Dr. Abhijit Sen (pathologist) for their guidance during analysis of the problem domain. This work is a part of the project work “An intelligent Telehealth system for pediatric Tuberculosis prediction and compatible for Tuberculosis footprint preparation”, in association with Nil Ratan Sircar Medical College and Hospital, Kolkata. The sample slides used for this work are collected from the associated hospital. Authors are thankfully acknowledging their support. Authors are grateful to Department of Computer Science and Engineering, Jadavpur University, Kolkata for creating the required infrastructural facilities.

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The online version contains supplementary material available at (https://doi.org/10.1007/s10916-020-01688-2)

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Authors and Affiliations

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

    Pramit Ghosh

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

    Debotosh Bhattacharjee & Mita Nasipuri

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  1. Pramit Ghosh
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  2. Debotosh Bhattacharjee
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Correspondence to Pramit Ghosh.

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This research work is a part of the work “An intelligent Telehealth System for Pediatric Tuberculosis Prediction and compatible for Tuberculosis Footprint Prediction”, which has the ethical approval (No/NMC/4004).

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The authors declare that they have no conflict of interest.

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Ghosh, P., Bhattacharjee, D. & Nasipuri, M. Passive Auto Focusing of Pathological Microscope with Intelligent Field Image Collection Mechanism. J Med Syst 45, 25 (2021). https://doi.org/10.1007/s10916-020-01688-2

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