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brain-tumor-detection

Brain Tumor is one the most deadly disease whose detection and treatment is one of the toughest tasks. At present, treatment of patients requires clinical pictures examination and is becoming a critical field. It fuses a wide scope of imaging procedures some of them are Computed Tomography channels (CT examines), Magnetic Resonance Imaging (MRIs) and X-columns and so forth. Medical experts perform tumor segmentation on data obtained from magnetic resonance imaging (MRI) which is very time consuming. Brain tumor segmentation is a significant process to extract information from complex MRI of brain image. Segmentation assessment is done by human, which can involve human errors in the result. So we have choose this topic because it is one of the most difficult and trending arena whose precision is the most important thing than any think else. So we implemented the detection using 2 ways the first one is the OpenCV method done using python. It takes MRI image as input and performs basic pre-processing. We have also implemented another process using or a way without using any big standard library and using convolution and integrated with machine leaning this predicts, the presence of the tumor region in the brain. This 2 method help us to detect the basic region where the tumor is present and highlights the region where the tumor is present. So this in a good way and highly précised way for the detection of the tumor in the MRI images of the brain. Doing it technically reduces the chance of error in a very great manner.

cpp-questions-and-solutions

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da1-nlp-explore-brown-and-guttenberg-corpus

Utilize Python NLTK (Natural Language Tool Kit) Platform and installing relevant Packages and Libraries and Exploring the Treebank corpora available in NLTK .

employee-attrition-analysis-and-prediction-using-supervised-ml

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An implementation to help out students and employees to maintain and keep notes of important head and paras so that it becomes easier to manage and plan the study/work schedule.

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