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Accurate segmentation of inflammatory and abnormal regions using medical thermal imagery

Australasian Physical & Engineering Sciences in Medicine volume 42, pages 647–657 (2019)Cite this article

Abstract

Methodologies reported in the existing literature for identification of a region of interest (ROI) in medical thermograms suffer from over- and under-extraction of the abnormal and/or inflammatory region, thereby causing inaccurate diagnoses of the spread of an abnormality. We overcome this limitation by exploiting the advantages of a logarithmic transformation. Our algorithm extends the conventional region growing segmentation technique with a modified similarity criteria and a stopping rule. In this method, the ROI is generated by taking common information from two independent regions produced by two different versions of a region-growing algorithm that use different parameters. An automatic multi-seed selection procedure prevents missed segmentations in the proposed approach. We validate our technique by experimentation on various thermal images of the inflammation of affected knees and abnormal breasts. The images were obtained from three databases, namely the Knee joint dataset, the DBT-TU-JU dataset, and the DMR-IR dataset. The superiority of the proposed technique is established by comparison to the performance of state-of-the-art competing methodologies. This study performed temperature emitted inflammatory area segmentation on thermal images of knees and breasts. The proposed segmentation method is of potential value in thermal image processing applications that require expediency and automation.

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Acknowledgements

The research work was supported by the Grant No. 5/7/1516/2016-RCH Dated: 20/06/2017 from the Indian Council of Medical Research (ICMR), Government of India.

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Authors and Affiliations

  1. Computer Science and Engineering, Tripura University, Suryamaninagar, Tripura, 799022, India

    Kakali Das, Mrinal Kanti Bhowmik & Omkar Chowdhuary

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

    Debotosh Bhattacharjee

  3. Department of Physics, Tripura University, Suryamaninagar, Tripura, 799022, India

    Barin Kumar De

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  1. Kakali Das
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Correspondence to Kakali Das.

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Ref. No.4(6-11)-AGMC/Medical Education/Ethics Com/2018/15136, Dated 31st December, 2018.

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Das, K., Bhowmik, M.K., Chowdhuary, O. et al. Accurate segmentation of inflammatory and abnormal regions using medical thermal imagery. Australas Phys Eng Sci Med 42, 647–657 (2019). https://doi.org/10.1007/s13246-019-00753-6

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