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Enhanced vascular and osseous information fusion: disagreement of quantitative and qualitative analysis

  • Recent Advances in Deep Learning for Medical Image Processing
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Abstract

The computer-aided algorithms are becoming indispensable in the field of digital subtraction angiography for better subsequent clinician diagnosis and feature extraction. These tools find widespread application for localization and highlighting potential malfunctioned sites and abnormal vascular pathology. For this purpose, an enhancement filter function based on Hessian matrix is often employed which produces a response close to ideal enhancement function in the literature. However, while predicting the abnormal pathology, both vessel and osseous details are elementary to patient diagnosis and treatment. In this manuscript, with an aim to parallelize the visualization of enhanced vessel details and osseous information for quick diagnosis, an image fusion algorithm is proposed based on the pre-enhancement of source images which generates highly pleasant visual results free from noise and ghostly artefacts outperforming the ten other image fusion techniques. Besides, this study presents a potential research challenge of disagreement between objective and subjective evaluation of fused image.

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Funding

This work is supported by University Grant Commission, Government of INDIA.

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Authors and Affiliations

  1. UIET, Panjab University, Chandigarh, India

    Ayush Dogra, Bhawna Goyal & Sunil Agrawal

  2. Computer Science and Information Systems, Texas A&M University-Commerce, Commerce, TX, USA

    Urcun John Tanik

  3. CSIR-Central Scientific Instruments Organization (CSIR-CSIO), Chandigarh, India

    Sanjeev Kumar

  4. Information Science and Engineering, Canara Engineering College, Mangaluru, India

    Ramesh Sunder Nayak

Authors
  1. Ayush Dogra
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  2. Bhawna Goyal
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  3. Sunil Agrawal
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  4. Urcun John Tanik
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  5. Sanjeev Kumar
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  6. Ramesh Sunder Nayak
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Correspondence to Ayush Dogra.

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Dogra, A., Goyal, B., Agrawal, S. et al. Enhanced vascular and osseous information fusion: disagreement of quantitative and qualitative analysis. Neural Comput & Applic 32, 15885–15895 (2020). https://doi.org/10.1007/s00521-019-04259-w

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  • DOI: https://doi.org/10.1007/s00521-019-04259-w

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