Research article

A novel approach for detecting the presence of a lymphatic rosary in the iris using a 3-stage algorithm

  • Received: 10 June 2024 Revised: 27 September 2024 Accepted: 05 November 2024 Published: 21 November 2024
  • Lymphatic dysfunction is characterized by the sluggish movement of lymph fluids. It manifests as a “Lymphatic Rosary” in the iris which is often due to dehydration and inactivity. Detecting these signs early is crucial for diagnosis and treatment. Therefore, there is a need for an automated, accurate, and efficient method to detect lymphatic rosaries in the iris. This paper presents a novel approach for detecting a lymphatic rosary using advanced image processing techniques. The proposed method involves iris segmentation to isolate the iris from the eye, followed by normalization to standardize its structure, and concludes with the application of the modified Daugman method to identify the lymphatic rosary. This automated process aims to enhance the accuracy and reliability of detection by minimizing the subjectivity associated with manual analysis. The proposed approach was tested on various iris images and the results demonstrated impressive accuracy in detecting lymphatic rosaries. The use of different iris code bit representations allowed for a robust detection process, showcasing the method's effectiveness by achieving an accuracy of 94.5% in identifying the presence of a lymphatic rosary across different stages. The novel image processing technique outlined in this paper offers a promising solution for the automated detection of lymphatic rosaries in the iris. The approach not only improves diagnostic accuracy but also provides a standardized method that could be widely implemented in clinical settings. This advancement in iris diagnosis has the potential to play a significant role in the early detection and management of lymphatic dysfunction.

    Citation: Poovayar Priya Mohan, Ezhilarasan Murugesan. A novel approach for detecting the presence of a lymphatic rosary in the iris using a 3-stage algorithm[J]. AIMS Bioengineering, 2024, 11(4): 506-526. doi: 10.3934/bioeng.2024023

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  • Lymphatic dysfunction is characterized by the sluggish movement of lymph fluids. It manifests as a “Lymphatic Rosary” in the iris which is often due to dehydration and inactivity. Detecting these signs early is crucial for diagnosis and treatment. Therefore, there is a need for an automated, accurate, and efficient method to detect lymphatic rosaries in the iris. This paper presents a novel approach for detecting a lymphatic rosary using advanced image processing techniques. The proposed method involves iris segmentation to isolate the iris from the eye, followed by normalization to standardize its structure, and concludes with the application of the modified Daugman method to identify the lymphatic rosary. This automated process aims to enhance the accuracy and reliability of detection by minimizing the subjectivity associated with manual analysis. The proposed approach was tested on various iris images and the results demonstrated impressive accuracy in detecting lymphatic rosaries. The use of different iris code bit representations allowed for a robust detection process, showcasing the method's effectiveness by achieving an accuracy of 94.5% in identifying the presence of a lymphatic rosary across different stages. The novel image processing technique outlined in this paper offers a promising solution for the automated detection of lymphatic rosaries in the iris. The approach not only improves diagnostic accuracy but also provides a standardized method that could be widely implemented in clinical settings. This advancement in iris diagnosis has the potential to play a significant role in the early detection and management of lymphatic dysfunction.



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    Conflict of interest



    The authors declare that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper.

    Author contributions



    Poovayar Priya M. provided the conceptualization, investigation, methodology, implementation, validation, and visualization, and wrote the original draft; Ezhilarasan M. provided the validation and supervision.

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