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Study on Efficient DRLSE-Oriented Edge-Based Medical Image Segmentation of Cardiac Images

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Emerging Technologies in Data Mining and Information Security

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 164))

Abstract

Today, medical image-based processing is very much used in recent research in medical domain very effectively. So, this technical approach helps the medical expertise person to take faster decision regarding earlier diagnosis and faster decision regarding operation and next stages treatments. Level set approach is a crucial method that is used domain as computer vision. So, the normal level set approach is more error prone and creates several irregularities for the evolution in the stages of stabilities of algorithms. Here, the potential function is built and create a distance regularized term for making solution of initiating level set function in periodical way. A energy function is created by combining internal and external energy function. The main purpose of this task is medical image-based detection. The DRLSE-based segmentation approach reduces the re-initialization problems and can minimize the errors. The problems of further initialization can hamper the accuracy or rate of performance. This approach can efficiently able to initialize the level set value which is flexible to changing the time steps in a difference scheme for elimination of amount of iterations. The approach provides more than 85% overall accuracy and sensitivity scores for proper segmentation of the cardiac images in medical imaging domain. This approach can effectively segment the area of contour region to the boundary with varying number of iterations with lesser error rate.

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Acknowledgements

Here we acknowledge DoveMed [32–34] which is based on healthcare based technology which provides several hospital based information as of taking several cardiac MRI images which are very crucial parts of our research work. Several patients images are taken from this organization which are basically one of the healthcare based company portal quite user-friendly. A lot of medical images are used from them which are really effective for working with cardiac or ventricular related studies. Also some image datasets are taken from the blog of Dr. Paul Babyn, Radiologist-in-Chief, and Dr. Shi-Joon Yoo, Cardiac Radiologist of hospital of Toronto.

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Authors and Affiliations

  1. Department of Electronics and Tele Communication Engineering, Jadavpur University, Kolkata, India

    Pramit Brata Chanda & Subir Kumar Sarkar

Authors
  1. Pramit Brata Chanda
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  2. Subir Kumar Sarkar
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Correspondence to Subir Kumar Sarkar .

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Editors and Affiliations

  1. Faculdade de Engenharia da, Universidade do Porto, Porto, Portugal

    João Manuel R. S. Tavares

  2. Institute of Engineering and Management, Kolkata, West Bengal, India

    Satyajit Chakrabarti

  3. Institute of Engineering and Management, Kolkata, West Bengal, India

    Abhishek Bhattacharya

  4. Institute of Engineering and Management, Kolkata, West Bengal, India

    Sujata Ghatak

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Chanda, P.B., Sarkar, S.K. (2021). Study on Efficient DRLSE-Oriented Edge-Based Medical Image Segmentation of Cardiac Images. In: Tavares, J.M.R.S., Chakrabarti, S., Bhattacharya, A., Ghatak, S. (eds) Emerging Technologies in Data Mining and Information Security. Lecture Notes in Networks and Systems, vol 164. Springer, Singapore. https://doi.org/10.1007/978-981-15-9774-9_75

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