Automated Detection of False positives and false negatives in Cerebral Aneurysms from MR Angiography Images by Deep Learning Methods

摘要

Prediction is the vital process of introspecting any events, diseases and other applications. Sometime it became witness of abnormal outcome which yields improper decision on crucial part of life. False positive and False Negatives are such valuable factors which affecting the process of correct decision on finding a specific problems in human body. False Positive denotes wrong result because it was not an actual positive and similarly it was not an actual negative but False Negative would obtain in a result. These two parameters are considered major contribution in finding Cerebral Aneurysm from MRA images and the same images are tuned after prediction result for resolving False Positive and Negative prediction of diseases along with deep neural networks model. Deep Learning can able to perform like human being based on input given. Simulation was performed by feeding sample images to find the cerebral Aneurysm and the same intended to find False positive and Negative using MATLAB and AlexNet.