For the last many decades, the research is towards the classification of medical images in the early phase of its detection. But, the task becomes challenging due to the absence of the color information, like in natural scene images, and low illumination. In this paper, a multi-scale spectral approach is proposed for the classification of medical images. The proposed approach uses a dyadic filter bank extended to six scales for simultaneous modulation of the frequency and amplitude signal of the medical image. The modulated signal strength is used for enhancing the contrast of the image as a preprocessing step. The 32 bin spectral histogram is used to fetch the features using different modulation components at each scale of the dyadic filter bank. The proposed method has experimented with two medical imaging databases - one is malignant Brain tumor MRI scans collected from SMS medical college Jaipur. The second database is from the TCIA data repository having three datasets of Lung-CT and Brain MRI. These datasets have experimented with SVM using a quadratic kernel function. The experimental results show that the proposed approach fetches better textural information as compared with traditional texture analysis methods. Based on the analysis of the experimentation results, it is recommended that the use of the spectral features gives better early detection of the abnormalities for medical imaging datasets.
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The authors would like to thank all the individuals who provide their guidance in the implementation of this work.
The author(s) declared no potential conflicts of interest concerning the research, authorship, and/or publication of this article.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent was obtained from all individual participants included in the study. Moreover, the prior patient consent has been taken by the respective authorities of the hospital for the participation of their images in the research study and for publications. As per the commitment all the annotations from the images where the details of the patients like their names, initials, and other related information were removed before its use. Also, the study has been approved by the Institutional ethics committee of SMS Medical College Jaipur with a grant IRB number 2182.
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Vidyarthi, A. Multi-scale dyadic filter modulation based enhancement and classification of medical images. Multimed Tools Appl (2020). https://doi.org/10.1007/s11042-020-09357-9
- Filter bank
- Image enhancement
- Amplitude- Frequency modulation
- Medical imaging