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An Effective Lung Cancer Diagnosis Model Using Pre-Trained CNNs
《Computer Modeling in Engineering & Sciences》2025年第4期1129-1155,共27页Majdi Rawashdeh Muath A.Obaidat Meryem Abouali Dhia Eddine Salhi Kutub Thakur 
Cancer is a formidable andmultifaceted disease driven by genetic aberrations and metabolic disruptions.Around 19% of cancer-related deaths worldwide are attributable to lung and colon cancer,which is also the top caus...
关键词:Lung cancer machine learning computer aided diagnosis CNN medical imaging transfer learning 
TC-Fuse: A Transformers Fusing CNNs Network for Medical Image Segmentation
《Computer Modeling in Engineering & Sciences》2023年第11期2001-2023,共23页Peng Geng Ji Lu Ying Zhang Simin Ma Zhanzhong Tang Jianhua Liu 
supported in part by the National Natural Science Foundation of China under Grant 61972267;the National Natural Science Foundation of Hebei Province under Grant F2018210148;the University Science Research Project of Hebei Province under Grant ZD2021334;the Science and Technology Project of Hebei Education Department(ZD2022098).
In medical image segmentation task,convolutional neural networks(CNNs)are difficult to capture long-range dependencies,but transformers can model the long-range dependencies effectively.However,transformers have a fle...
关键词:TRANSFORMERS convolutional neural networks fusion medical image segmentation axial attention 
An Interpretable CNN for the Segmentation of the Left Ventricle in Cardiac MRI by Real-Time Visualization被引量:1
《Computer Modeling in Engineering & Sciences》2023年第5期1571-1587,共17页Jun Liu Geng Yuan Changdi Yang Houbing Song Liang Luo 
The National Natural Science Foundation of China (62176048)provided funding for this research.
The interpretability of deep learning models has emerged as a compelling area in artificial intelligence research.The safety criteria for medical imaging are highly stringent,and models are required for an explanation...
关键词:Interpretable graphics training VISUALIZATION image segmentation left ventricle CNNS global average pooling 
Deep Learning-Based Cancer Detection-Recent Developments,Trend and Challenges被引量:2
《Computer Modeling in Engineering & Sciences》2022年第3期1271-1307,共37页Gulshan Kumar Hamed Alqahtani 
Cancer is one of the most critical diseases that has caused several deaths in today’s world.In most cases,doctors and practitioners are only able to diagnose cancer in its later stages.In the later stages,planning ca...
关键词:Autoencoders(AEs) cancer detection convolutional neural networks(CNNs) deep learning generative adversarial models(GANs) machine learning 
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