DenseUNet+: A novel hybrid segmentation approach based on multi-modality images for brain tumor segmentation
-
Published:2023-09
Issue:8
Volume:35
Page:101663
-
ISSN:1319-1578
-
Container-title:Journal of King Saud University - Computer and Information Sciences
-
language:en
-
Short-container-title:Journal of King Saud University - Computer and Information Sciences
Author:
Çetiner HalitORCID, Metlek SedatORCID
Subject
General Computer Science
Reference62 articles.
1. Brain Tumor Imaging: Applications of Artificial Intelligence;Afridi;Semin. Ultrasound, CT MRI,2022 2. TPCNN: Two-path convolutional neural network for tumor and liver segmentation in CT images using a novel encoding approach;Aghamohammadi;Expert Syst. Appl.,2021 3. Ahmad, P., Qamar, S., Shen, L., Rizvi, S.Q.A., Ali, A., Chetty, G., 2022. MS UNet: Multi-scale 3D UNet forBrain Tumor Segmentation BT - Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. In: Crimi, A., Bakas, S. (Eds.), . Springer International Publishing, Cham, pp. 30–41. 4. Akbar, A.S., Fatichah, C., Suciati, N., 2022b. Unet3D withMultiple Atrous Convolutions Attention Block forBrain Tumor Segmentation BT - Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. In: Crimi, A., Bakas, S. (Eds.), Springer International Publishing, Cham, pp. 182–193. 5. Single level UNet3D with multipath residual attention block for brain tumor segmentation;Akbar;J. King Saud Univ. - Comput. Inf. Sci.,2022
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|