Contextual information extraction in brain tumour segmentation

Authors: Maryam Zia, Usman Ali Baig, Zaka Ur Rehman, Muhammad Yaqub, Shahzad Ahmed, Yudong Zhang, Shuihua Wang‎, Rizwan Khan

Source: IET Image Processing, Vol 17, Iss 12, Pp 3371-3391 (2023)

Subject Terms: Artificial intelligence, MRI Segmentation, Brain Tumors, Geometry, Classification of Brain Tumor Type and Grade, attention gate, 02 engineering and technology, Image Segmentation, Pattern recognition (psychology), Feature Extraction, Dropout (neural networks), QA76.75-76.765, 03 medical and health sciences, 0302 clinical medicine, Segmentation, Context (archaeology), convolutional neural networks, Machine learning, Photography, 0202 electrical engineering, electronic engineering, information engineering, FOS: Mathematics, Image Segmentation Techniques, Computer software, modified 3D U‐net, TR1-1050, 10. No inequality, Biology, Voxel, Life Sciences, Paleontology, context aware 3D ARDUNet, Computer science, attentional residual dropout block, 3. Good health, Algorithm, Neurology, residual dropout block, Residual, Computer Science, Physical Sciences, Deep Learning in Computer Vision and Image Recognition, Semantic Segmentation, Computer vision, Computer Vision and Pattern Recognition, Block (permutation group theory), Mathematics, Neuroscience

Access URL: https://doaj.org/article/9e805cad93cd42bda299c7f9594c4ed2