Madurai Star Students Projects

In the existing system is based on single threshold based execution so it does not identify diseases. Single threshold segmentation method is not applicable of multi-channel image and characters are not very different from the images, for gray-scale images do not exist significant differences nor has a bigger overlap region of gray value images is difficult to get accurate results.Madurai Star Students ProjectsIn our proposed system is based on multiple threshold value based execution, so we can identify the changes occur on the lungs due to disease affection.We find the contour of each region using boundary tracking method. Then calculate the area of each contour and remove the smaller area according the condition. At last we can obtain the two largest areas which are the two contours of the pulmo. Set 1 is the value of inside contour and set null is the value of outside contour. Operation with the original image then we can get the image of lung parenchyma.

Madurai Star Students Projects

The automatic segmentation algorithm can get rid of the background interference and the interference of the trachea bronchus within the chest. It can segment the lung regions from the chest CT images automatically and accurately. It can be used in the lung area automatic extraction of computer-aided diagnosis.Threshold binarization, extract the boundary to remove the background of the trunk, threshold binarization after get rid of the background, lung parenchyma extraction, and lung area repair and so on. After remove the background interference Using trunk boundary and original image obtain the image without interference, and then use the optimal threshold value method again.

Madurai Star Students Projects

Madurai Star Students Projects

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