Results 111 to 120 of about 206,029 (232)

Leakage‐Controlled Evaluation of Pixel‐Level MRI–sCT Fusion Reveals a Quality–Performance Mismatch in Brain Tumour Classification

Vector: The Journal of Engineering, Volume 2027, Issue 1, January/December 2027.
This study presents a leakage‐free evaluation of pixel‐level MRI–synthetic CT fusion for brain tumour classification using EfficientNet‐B0, image‐quality metrics, statistical testing and Grad‐CAM explainability. The results show that although fusion methods improved several image‐quality measures, none outperformed MRI‐only classification in accuracy ...
Muazzam Ali, Muhammad Usman Hashmi, Muhammad Azam, Raheem Sarwar   +3 more
wiley   +1 more source

Cross‐Modal Artificial Intelligence Integrating Dynamic MRI and Clinical Data for Breast Cancer Diagnosis and Nodal Metastasis Prediction

MedComm – Oncology, Volume 5, Issue 4, December 2026.
A multicenter artificial intelligence framework was developed and externally validated for breast lesion classification and axillary lymph node metastasis prediction. Using dynamic contrast‐enhanced MRI alone for lesion classification and integrating MRI with preoperative clinical and biopsy‐derived information for nodal prediction, the framework ...
Wei Ren, Zifan He, Zhixian Deng, Zhenjun Huang, Gengxi Cai, Xiaohua Ban, Qiugen Hu, Zebang Zhang, Luhui Mao, Yujie Tan, Qing Peng, Zehua Wang, Ruichong Lin, Xian Yang, Xiaohui Duan, Herui Yao, Yunfang Yu   +16 more
wiley   +1 more source

Uncertainty‐aware hybrid model for reliable navigation guidance in prostate biopsy

Medical Physics, Volume 53, Issue 11, November 2026.
Abstract Background Prostate biopsy – performed under ultrasound (US) guidance ‐ is the only confirmatory procedure for diagnosing prostate cancer. If several systems aiming at improving the accuracy of tissue sampling for histopathological analysis exist, they often fail to adequately account for patient / tissue motion and deformation during the ...
Chloé Soormally, Clément Beitone, Jocelyne Troccaz, Sandrine Voros   +3 more
wiley   +1 more source

Transfer Learning With U-Swin Transformer for Adaptive Ground Roll Attenuation in Seismic Records From Sabkha Environments

IEEE Access
Ground roll is a dominant coherent noise in land seismic data, characterized by low frequency, low velocity, and high amplitude. often overlaps with reflection arrivals, thereby reducing the reliability of seismic imaging and interpretation.
Ahmed Eleslambouly, Guibin Zhao, Fateh Bouchaala, Mohammed Y. Ali, Jun Matsushima   +4 more
doaj   +1 more source

EA-Swin: An Embedding-Agnostic Swin Transformer for AI-Generated Video Detection

CoRR
Recent advances in foundation video generators such as Sora2, Veo3, and other commercial systems have produced highly realistic synthetic videos, exposing the limitations of existing detection methods that rely on shallow embedding trajectories, image-based adaptation, or computationally heavy MLLMs.
Hung Mai, Loi Dinh, Duc Hai Nguyen, Dat Do, Luong Doan, Khanh Nguyen Quoc, Huan Vu, Phong Ho, Naeem Ul Islam, Tuan Do   +9 more
openaire   +2 more sources

Probing Atmospheric Gravity‐Wave‐Relevant Representations in a Weather Foundation Model via Multi‐Method Fine‐Tuning

Geophysical Research Letters, Volume 53, Issue 20, 28 October 2026.
Abstract Weather foundation models pretrained on reanalysis data may encode subgrid‐scale physics beyond their forecasting objectives. Using Aurora, we probe this with a multi‐method fine‐tuning framework: agreement across structurally different adaptation strategies signals shared backbone information, while a matched randomly initialized control ...
Yanan Guo, Junqiang Song, Chuanfeng Zhao, Xiaoqun Cao, Yikun Yang, Hongze Leng   +5 more
wiley   +1 more source

Swin Routiformer: Moss Classification Algorithm Based on Swin Transformer With Bi-Level Routing Attention

IEEE Access
Accurate classification of moss species is essential for progress in ecology and biology. However, traditional methods for classifying moss require significant expertise, and current deep learning techniques struggle due to limited dataset diversity and ...
Peichen Li, Huiqin Wang, Zhan Wang, Ke Wang, Chong Wang   +4 more
doaj   +1 more source

Beyond Pigment Loss: Integrating Clinician‐Reported Outcomes, Patient‐Reported Outcomes, and Digital Biometrics to Quantify Vitiligo Morbidity

Dermatological Reviews, Volume 7, Issue 5, October 2026.
ABSTRACT Background Vitiligo is an autoimmune depigmenting disease with multiple facets to disease severity. Accurate assessment of severity and therapeutic response is essential for both clinical care and research. Methods This narrative review summarizes outcome measures for assessing different aspects of vitiligo severity, including extent, activity,
Shrruthi Velavan, Vishal Gupta
wiley   +1 more source

SE‐Swin: An improved Swin‐Transfomer network of self‐ensemble feature extraction framework for image retrieval

IET Image Processing
The Swin‐Transformer is a variant of the Vision Transformer, which constructs a hierarchical Transformer that computes representations with shifted windows and window multi‐head self‐attention.
Yixuan Xu, Xianbing Wang, Hua Zhang, Hai Lin   +3 more
doaj   +1 more source

Memorizing Swin-Transformer Denoising Network for Diffusion Model

Diffusion models have garnered significant attention in the field of image generation. However, existing denoising architectures, such as U-Net, face limitations in capturing the global context, while Vision Transformers (ViTs) may struggle with local ...
Yiqing Shen, Jindou Chen
core   +1 more source