Double Stage Guassian Filtering and Marker Controlled Watershed Transform based Deep Learning Technique to automatically Detect Liver Cancer Using CT Scan Images
Keywords:
DCNN Model, Liver Cancer, Marker Controlled Watershed transform, Double stage Guassian FilterAbstract
According to a survey conducted by Globocon 2020, Liver Cancer was the sixth biggest reason of death globally due to deaths caused by cancer. Another survey concluded that early detection of liver cancer increases survival rate of persons suffering from cancer. Traditional methods are not as fast and conclusive, Hence we propose a Computer Aided Diagnosis(CAD) method for early detection and treatment of liver cancer. Proposed method is based on Double Stage Guassian Filtering and Marker Controlled Watershed Transform based Deep Learning Technique. It is a two step process where pre-processing and segmentation is performed in first step and classification is performed in next step. 200 clinical and 200 secondary data from LiTs data set was used to train, test and validate our model. Proposed model achieved 96.42 % accuracy for primary dataset and 96.66 % accuracy for secondary data set. Our model is ready to be tested on bigger dataset and can be deployed at imaging centres in near future..
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Copyright (c) 2023 Mohammad Anwarul Siddique, Shailendra Kumar Singh, Moin Hasan, Tanveer Quazi
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