Brain tumor segmentation and detection is one of the most critical parts in the field of medical regions. Tumor is a cancer type that can be visible in any part of the body in case of primary and secondary tumor. The different type of brain tumor is glioma, benign, malignant, meningioma. This research helps in retrieving the tumor region in the brain with the help of 2D MRI images. The system predicts using MATLAB which is a programming platform and analyze the tumor from different method like canny edge, Otsu's binary, fuzzy c-means (FCM), and k-means clustering to improve the borders using the pixel technique. Using convolution neural network (CNN), neural network, and natural language processing, the system detects brain tumor based on the pre-processing and post-processing feature. Moreover, the authors figure out which tumor affected is the most important feature to protect the lifespan in the initial stages. Finally, it acknowledges the result in the mail format to the doctor or patient.
Ksheera Dhooma is an effective and popular Ayurvedic procedure in which decoction of herbal medicines and cow’s milk are mixed, heated and the emitted vapours are directed through a rubber tube. The steam coming out of the tube is applied to the whole body or the affected part of the patient’s body. It is used in the treatment of facial paralysis, lock jaw and disorders of head and neck, with Vata Dosha imbalance. Though Ksheera Dhooma is considered as a type of Sweda, it is termed as Dhooma because steam is inhaled with gaping mouth. Ksheera Dhooma has multi-fold benefits like facilitating proper blood circulation of the body and relaxation of the mind, lubrication of the joints, relief from pain, spasms and stiffness of the muscles and joints. This study was performed with an aim to review the procedure of Ksheera Dhooma or Palpuka Swedam, understand the standard operating procedure and its efficacy.
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