Liver-Tumor Detection Using CNN ResUNet

查看全文 作　　者：Muhammad Sohaib [1]Aslam;Muhammad [1]Younas;Muhammad Umar [1]Sarwar;Muhammad Arif [2]Shah;Atif [3]Khan;MIrfan [4]Uddin;Shafiq [5]Ahmad;Muhammad [5]Firdausi;Mazen [6]Zaindin

机构地区：[1]Department of Computer Science,Government College University Faisalabad,Faisalabad,38000,Pakistan;[2]Department of IT and Computer Science,Pak-Austria Fachhochschule Institute of Applied Sciences and Technology,Haripur,22620,Pakistan;[3]Department of Computer Science,Islamia College Peshawar,Peshawar,KP,Pakistan;[4]Institute of Computing,Kohat University of Science and Technology,Kohat,Pakistan;[5]Department of Industrial Engineering,College of Engineering,King Saud University,Riyadh,11421,Saudi Arabia;[6]Department of Statistics and Operations Research,College of Science,King Saud University,Riyadh,11421,Saudi Arabia

出　　处：《Computers, Materials & Continua》索引2021年第5期,共16页

基　　金：The authors extend their appreciation to the Deanship of Scientific Research at King Saud University for funding this work through research group No RG-1438-089. 摘　　要：Liver tumor is the fifth most occurring type of tumor in men and the ninth most occurring type of tumor in women according to recent reports of Global cancer statistics 2018.There are several imaging tests like Computed Tomography(CT),Magnetic Resonance Imaging(MRI),and ultrasound that can diagnose the liver tumor after taking the sample from the tissue of the liver.These tests are costly and time-consuming.This paper proposed that image processing through deep learning Convolutional Neural Network(CNNs)ResUNet model that can be helpful for the early diagnose of tumor instead of conventional methods.The existing studies have mainly used the two Cascaded CNNs for liver segmentation and evaluation of Region Of Interest(ROI).This study uses ResUNet,an updated version of U-Net and ResNet Models that utilize the service of Residential blocks.We apply over method on the 3D-IRCADb01 dataset that is based on CT slices of liver tumor affected patients.The results showed the True Value Accuracy around 99%and F1 score performance around 95%.This method will be helpful for early and accurate diagnose of the Liver tumor to save the lives of many patients in the field of Biotechnology. 关键词：LIVER TUMOR DIAGNOSE ResUNet CNNS SEGMENTATION

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Liver-Tumor Detection Using CNN ResUNet

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