Transfer learning for segmentation with hybrid classification to Detect Melanoma Skin Cancer.

Melanoma is an abnormal proliferation of skin cells that arises and develops in most of the cases on surface of skin that is exposed to copious amounts of sunlight. This common type of cancer may develop in areas of the skin that are not exposed to a much abundant sunlight. The research addresses the problem of Segmentation and Classification of Melanoma Skin Cancer. Melanoma is the fifth most common skin cancer lesion. Bio-medical Imaging and Analysis has become more promising, interesting, and beneficial in recent years to address the eventual problems of Melanoma Skin Cancerous Tissues that may develop on Skin Surfaces. The evolved research finds that Attributes Selected for Classification with Color Layout Filter model. The research has produced an optimal result in terms of certain performance metrics accuracy, precision, recall, PRC (what is PRC? Expansion is needed in Abstract), The proposed method has yielded 90.96% of accuracy and 91% percent of precise and 0.91 of recall out of 1.0, 0.95 of ROC AUC, 0.87 of Kappa Statistic, 0.91 of F-Measure. It has been noticed a lowest error with reference to proposed method on certain dataset. Finally, this research recommends that the Attribute Selected Classifier by implementing one of the image enhancement techniques like Color Layout Filter is showing an efficient outcome.

Magnetic resonance imaging in rhino-orbital-cerebral mucormycosis.

Coronavirus disease-associated mucormycosis (CAM) is an established clinical entity in India. In the past 4 months, there has been a sharp upsurge in the number of CAM cases in most parts of the country. Early diagnosis can be lifesaving. Magnetic resonance imaging (MRI) imaging remains the corner stone of management in patients with ROCM. This review discussed the utility of MRI imaging in ROCM with an emphasis on the ideal MRI protocol in a suspected case of ROCM, the pathways of spread of infection, the classic diagnostic features, MRI for staging of the disease, MRI for prognostication, MRI for follow up, and imaging features of common differentials in ROCM. The pit falls of MRI imaging and a comparison of CT and MRI imaging in ROCM are discussed. The clinical interpretation of areas of contrast uptake and those of necrosis and its relevance to treatment are discussed. This review aims to familiarize every member of the multidisciplinary team involved in managing these patients to be able to interpret the findings on MRI in ROCM.