Results 101 to 110 of about 8,876 (216)

GBT‐SAM: A Parameter‐Efficient Depth‐Aware Model for Generalizable Brain Tumor Segmentation on mp‐MRI

International Journal of Imaging Systems and Technology, Volume 36, Issue 4, July 2026.
ABSTRACT Gliomas are aggressive brain tumors that require accurate imaging‐based diagnosis, where automated segmentation plays a central role in assessing tumor morphology and guiding treatment decisions. Manual delineation of gliomas is time‐consuming and prone to variability, motivating the use of deep learning to improve consistency and alleviate ...
Cecilia Diana‐Albelda, Roberto Alcover‐Couso, Álvaro García‐Martín, Jesus Bescos, Marcos Escudero‐Viñolo   +4 more
wiley   +1 more source

A self attention based deep learning framework for accurate and efficient dental disease detection in OPG radiographs

Scientific Reports
Oral diseases are increasing now-a-days and there is a high demand for the automatic diagnostic system that helps the clinician to detect these oral diseases with more accuracy and reduced human error.
Ramasubramanian Bhoopalan, S. Mirdula, Priyadharshini Kannusamy, D. Gayathri, D. Manikandan, Krishnaraj Ramaswamy   +5 more
doaj   +1 more source

A New Subject-Sensitive Hashing Algorithm Based on Multi-PatchDrop and Swin-Unet for the Integrity Authentication of HRRS Image

ISPRS International Journal of Geo-Information
Transformer-based subject-sensitive hashing algorithms exhibit good integrity authentication performance and have the potential to ensure the authenticity and convenience of high-resolution remote sensing (HRRS) images.
Kaimeng Ding, Yingying Wang, Chishe Wang, Ji Ma   +3 more
doaj   +1 more source

Benchmarking Hybrid CNN‐Transformer Versus Pure Transformer Architectures for Accelerated Hyperpolarized 129Xe MRI Reconstruction

Journal of Magnetic Resonance Imaging, Volume 64, Issue 1, Page 266-280, July 2026.
ABSTRACT Background Hyperpolarized 129Xe MRI faces technical challenges including low signal‐to‐noise ratio and breath‐hold constraints. Current literature focuses on proprietary deep learning methods or image‐domain enhancements. Purpose To present a comprehensive evaluation of transformer and hybrid CNN‐transformer architectures integrating dual ...
Ramtin Babaeipour, Matthew S. Fox, Grace Parraga, Alexei Ouriadov   +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

Generative Artificial Intelligence and Large Language Models in Clinical Oncology

MedComm, Volume 7, Issue 7, July 2026.
By integrating multimodal data, including medical imaging, pathology, omics, and electronic health records, generative AI and LLMs support cancer diagnosis, treatment planning, and follow‐up management. These technologies also enhance physician–patient communication, improve personalized treatment strategies, and leverage intelligent agent automation ...
Yunfang Yu, Zhenhui Zhao, Zehua Wang, Ruichong Lin, Yujie Tan, Yongjian Chen, Ting Li, Daniel Baptista‐Hon, Xiaoxi Zhang, Chuan Wu, Man Tong, Lijun Zheng, Junyan Wu, Olivia Monteiro, Kang Zhang   +14 more
wiley   +1 more source

A pipeline to compile expert‐verified datasets of digitised herbarium specimens for automated plant identification to accelerate taxonomy

PLANTS, PEOPLE, PLANET, Volume 8, Issue 4, Page 1145-1159, July 2026.
Understanding and protecting plant life is essential for tackling the twin challenges of biodiversity loss and climate change. To support this, we have developed a new digital approach that helps identify plant species more quickly and accurately.
Jed Arno, Jérémie Morel, Fitiavana Rasaminirina, Juliene de Fátima Maciel‐Silva, Daniel Cahen, Damon P. Little, Daniele Silvestro, Alexandre Antonelli, Olwen Grace, Li Zhang, Isabel Larridon   +10 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

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

Transformers meet CNNs for insights into breast mass classification from histopathological images

Frontiers in Artificial Intelligence
IntroductionBreast cancer remains one of the leading causes of cancer-related deaths among women worldwide, highlighting the critical need for accurate histopathological diagnosis and reliable decision-support systems to improve diagnostic sensitivity ...
Vatsala Anand, Ajay Khajuria
doaj   +1 more source