Comprehensive Review on MRI-Based Brain Tumor Segmentation: A Comparative Study from 2017 Onwards
Brain tumor segmentation has been a challenging and popular research problem in the area
of medical imaging and computer-aided diagnosis. In the last few years, especially since …
of medical imaging and computer-aided diagnosis. In the last few years, especially since …
A diagnostic report supervised deep learning model training strategy for diagnosis of COVID-19
S Deng, X Zhang, S Jiang - Pattern Recognition, 2024 - Elsevier
COVID-19 is a highly contagious infectious disease that necessitates timely assessment and
effective diagnosis, although it is no longer a health emergency. Most existing computer …
effective diagnosis, although it is no longer a health emergency. Most existing computer …
Utilizing photosynthetic oxygen-releasing biomaterials to modulate blood vessel growth in the chick embryo chorioallantoic membrane
Z Wang, X Miao, X Wu, Y Wu, T Han, Y Su, P Liu… - Biomaterials …, 2025 - pubs.rsc.org
Effective vascularization is crucial for the success of tissue engineering and is influenced by
numerous factors. The present work focuses on investigating the effect of a substance …
numerous factors. The present work focuses on investigating the effect of a substance …
[HTML][HTML] Development and validation of a fully automatic tissue delineation model for brain metastasis using a deep neural network
JY Zhao, Q Cao, J Chen, W Chen, SY Du… - … Imaging in Medicine …, 2023 - ncbi.nlm.nih.gov
Background Stereotactic radiosurgery (SRS) treatment planning requires accurate
delineation of brain metastases, a task that can be tedious and time-consuming. Although …
delineation of brain metastases, a task that can be tedious and time-consuming. Although …
多模态MRI 脑肿瘤分割方法的特征融合技术综述.
刘海超， 宋丽娟 - Journal of Computer Engineering & …, 2024 - search.ebscohost.com
随着人工智能技术的快速发展, 脑肿瘤分割在提高临床诊断, 研究和治疗的准确性和效率方面
取得了显著进展. 多模态医疗图像分割正在成为当前脑肿瘤分割研究的热点和趋势 …
取得了显著进展. 多模态医疗图像分割正在成为当前脑肿瘤分割研究的热点和趋势 …
[HTML][HTML] Dilated multi-scale residual attention (DMRA) U-Net: three-dimensional (3D) dilated multi-scale residual attention U-Net for brain tumor segmentation
L Zhang, Y Li, Y Liang, C Xu, T Liu… - Quantitative Imaging in …, 2024 - pmc.ncbi.nlm.nih.gov
Background The precise identification of the position and form of a tumor mass can improve
early diagnosis and treatment. However, due to the complicated tumor categories and …
early diagnosis and treatment. However, due to the complicated tumor categories and …
Enhancing automatic prediction of clinically significant prostate cancer with deep transfer learning 2.5-dimensional segmentation on bi-parametric magnetic …
M Li, N Ding, S Yin, Y Lu, Y Ji… - Quantitative Imaging in …, 2024 - pmc.ncbi.nlm.nih.gov
Background The aggressiveness of prostate cancer (PCa) is crucial in determining treatment
method. The purpose of this study was to establish a 2.5-dimensional (2.5 D) deep transfer …
method. The purpose of this study was to establish a 2.5-dimensional (2.5 D) deep transfer …
Integrating a deep neural network and Transformer architecture for the automatic segmentation and survival prediction in cervical cancer
S Zhu, L Lin, Q Liu, J Liu, Y Song… - Quantitative Imaging in …, 2024 - pmc.ncbi.nlm.nih.gov
Background Automated tumor segmentation and survival prediction are critical to clinical
diagnosis and treatment. This study aimed to develop deep-learning models for automatic …
diagnosis and treatment. This study aimed to develop deep-learning models for automatic …