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Multi photon micro material analysis based on Raman spectroscopy biosensor for cancer detection using biomarker with deep learning techniques

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Abstract

Due to singularity of Raman Spectroscopy (RS) measurements in revealing molecular biochemical changes between cancerous and normal tissues and cells, RS was recently demonstrated to be a non-destructive method of cancer diagnosis. The quantity and quality of tissue samples for RS are crucial for accurate prediction when developing computational methods for cancer detection. The training of the classifier with a small number of samples is difficult and frequently leads to overfitting. As a result, increasing the number of samples is crucial for better training classifiers that can accurately classify cancer tissue. This study proposes a novel method for the detection of spine cancer using a high-sensitivity biosensor and edge elimination based on Raman spectroscopy by Multi photon micro material analysis. Using a high-sensitivity biosensor and Raman spectroscopy, the input tumour image edge is removed. F-fluorodeoxy glucose PET imaging (FDG-PET) applied images are used to identify the cancer-affected region in this edge-minimized image, and a Lasso regressive-based reinforcement neural network is used to analyse the 511-keV photons. The accuracy, F-measure, recall, dice coefficient, Areas under the curve (AUC), and neuron-specific enolase (NSE) are all used in the experimental analysis. proposed technique attained accuracy of 98%, F-measure of 75%, Recall of 65%, dice coefficient of 55%, AUC of 63% and NSE of 59%.

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Authors and Affiliations

  1. Department of Physics and Electronics, School of Sciences, Jain (Deemed to Be University), JC Road, Bangalore, 560027, India

    Asha Rajiv

  2. Department of Computer Science and IT, Arka Jain University, Jamshedpur, Jharkhand, India

    Alka Kumari

  3. Department of Chemistry, Teerthanker Mahaveer University, Moradabad, Uttar Pradesh, India

    Atri Deo Tripathi

  4. Department of Chemistry, Vivekananda Global University, Jaipur, India

    Menka Bhasin

  5. Department of Computer Science and Engineering, Parul Institute of Engineering and Technology, Parul University, Vadodara, Gujarat, India

    Vipul Vekariya

  6. Department of Management, Sanskriti University, Mathura, Uttar Pradesh, India

    Rajesh Gupta

  7. School of Engineering and Computing, Dev Bhoomi Uttarakhand University, Dehradun, Uttarakhand, India

    Digvijay Singh

Authors
  1. Asha Rajiv
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  2. Alka Kumari
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  3. Atri Deo Tripathi
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  4. Menka Bhasin
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  5. Vipul Vekariya
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  6. Rajesh Gupta
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  7. Digvijay Singh
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Contributions

AR: Conceived and design the analysis. AK: Writing—Original draft preparation. ADT: Collecting the Data, MB: Contributed data and analysis stools, VV Performed and analysis, RG: Performed and analysis, DS: Wrote the Paper, Editing and Figure Design.

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Correspondence to Asha Rajiv.

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Rajiv, A., Kumari, A., Tripathi, A.D. et al. Multi photon micro material analysis based on Raman spectroscopy biosensor for cancer detection using biomarker with deep learning techniques. Opt Quant Electron 55, 1163 (2023). https://doi.org/10.1007/s11082-023-05386-4

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  • DOI: https://doi.org/10.1007/s11082-023-05386-4

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