to download project abstract


There is lot of progress made in the field of treatment of lung cancer in the last years
(adjustment chemotherapy, radio therapy, individualized therapy). Nonetheless, lung
cancer is still remained the threat of society and cause of death of thousands of people
in all over the world. This paper is all about detection of lungs cancer. Here Computer
Tomography (CT) images are used to detect lungs cancer. There are several
algorithms are used to detect Lungs cancer accurately. Here sharp masking filter is
use to filtering the image. Adaptive Canny edge detection algorithm is used to detect
the edges and cancer affected areas. Neural network is used to classify the features
and predict the probability of lung cancer. K-Nearest Neighbors is used to segment
the cancer from lungs.

Past years have experienced increasing mortality rate due to lung cancer and thus it
becomes crucial to predict whether the tumor has transformed to cancer or notif the
prediction is made at an early stage then many lives can be saved and accurate
prediction also can help the doctors start their treatment. Computed tomography plays
a vital role in ensuring the condition of tumor that by checking the size of tumor,
location of tumor, etc

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