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  • Open Access


    Simulated Annealing with Deep Learning Based Tongue Image Analysis for Heart Disease Diagnosis

    S. Sivasubramaniam*, S. P. Balamurugan

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 111-126, 2023, DOI:10.32604/iasc.2023.035199

    Abstract Tongue image analysis is an efficient and non-invasive technique to determine the internal organ condition of a patient in oriental medicine, for example, traditional Chinese medicine (TCM), Japanese traditional herbal medicine, and traditional Korean medicine (TKM). The diagnosis procedure is mainly based on the expert's knowledge depending upon the visual inspection comprising color, substance, coating, form, and motion of the tongue. But conventional tongue diagnosis has limitations since the procedure is inconsistent and subjective. Therefore, computer-aided tongue analyses have a greater potential to present objective and more consistent health assessments. This manuscript introduces a novel Simulated Annealing with Transfer Learning… More >

  • Open Access


    Political Optimizer with Deep Learning-Enabled Tongue Color Image Analysis Model

    Anwer Mustafa Hilal1,*, Eatedal Alabdulkreem2, Jaber S. Alzahrani3, Majdy M. Eltahir4, Mohamed I. Eldesouki5, Ishfaq Yaseen1, Abdelwahed Motwakel1, Radwa Marzouk6

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1129-1143, 2023, DOI:10.32604/csse.2023.030080

    Abstract Biomedical image processing is widely utilized for disease detection and classification of biomedical images. Tongue color image analysis is an effective and non-invasive tool for carrying out secondary detection at anytime and anywhere. For removing the qualitative aspect, tongue images are quantitatively inspected, proposing a novel disease classification model in an automated way is preferable. This article introduces a novel political optimizer with deep learning enabled tongue color image analysis (PODL-TCIA) technique. The presented PODL-TCIA model purposes to detect the occurrence of the disease by examining the color of the tongue. To attain this, the PODL-TCIA model initially performs image… More >

  • Open Access


    Fusion Based Tongue Color Image Analysis Model for Biomedical Applications

    Esam A. AlQaralleh1, Halah Nassif2, Bassam A. Y. Alqaralleh2,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5477-5490, 2022, DOI:10.32604/cmc.2022.024364

    Abstract Tongue diagnosis is a novel and non-invasive approach commonly employed to carry out the supplementary diagnosis over the globe. Recently, several deep learning (DL) based tongue color image analysis models have existed in the literature for the effective detection of diseases. This paper presents a fusion of handcrafted with deep features based tongue color image analysis (FHDF-TCIA) technique to biomedical applications. The proposed FDHF-TCIA technique aims to investigate the tongue images using fusion model, and thereby determines the existence of disease. Primarily, the FHDF-TCIA technique comprises Gaussian filtering based preprocessing to eradicate the noise. The proposed FHDF-TCIA model encompasses a… More >

  • Open Access


    Intelligent Deep Learning Based Disease Diagnosis Using Biomedical Tongue Images

    V. Thanikachalam1,*, S. Shanthi2, K. Kalirajan3, Sayed Abdel-Khalek4,5, Mohamed Omri6, Lotfi M. Ladhar7

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5667-5681, 2022, DOI:10.32604/cmc.2022.020965

    Abstract The rapid development of biomedical imaging modalities led to its wide application in disease diagnosis. Tongue-based diagnostic procedures are proficient and non-invasive in nature to carry out secondary diagnostic processes ubiquitously. Traditionally, physicians examine the characteristics of tongue prior to decision-making. In this scenario, to get rid of qualitative aspects, tongue images can be quantitatively inspected for which a new disease diagnosis model is proposed. This model can reduce the physical harm made to the patients. Several tongue image analytical methodologies have been proposed earlier. However, there is a need exists to design an intelligent Deep Learning (DL) based disease… More >

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