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Diagnosis of lung cancer in its primal stage is a major problem faced by the medical world. For that proper details are needed from the images, which can only be obtained by a good segmentation method. However, many common forms of techniques are available in market and their major drawback is the accuracy of segmentation of the nucleus from the ROI and also the time consumed for the same. Since this...
Cervical cancer is one of the deadliest cancer known and is also a key research area in image processing. The main problem with this cancer is that it cannot be detected as it doesn't throw any symptoms until the final stages. This is attributed to the cancer itself and also to the lack of pathologists available to screen the cancer. Here we have proposed a novel approach to classify the various malignancies...
In this paper, we introduce a method of functionally classifying lung cancer cells from normal cells by using Tetrakis Carboxy Phenyl Porphine (TCPP) and well-known computational intelligent techniques. Tetrakis Carboxy Phenyl Porphine (TCPP) is a porphyrin that is able to label cancer cells due to the increased numbers of low density lipoproteins coating the surface of cancer cells and the porous...
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