On the challenges and perspectives of foundation models for medical image analysis
This article discusses the opportunities, applications and future directions of large-scale
pretrained models, ie, foundation models, which promise to significantly improve the …
pretrained models, ie, foundation models, which promise to significantly improve the …
Enhancing head and neck tumor management with artificial intelligence: Integration and perspectives
NN Zhong, HQ Wang, XY Huang, ZZ Li, LM Cao… - Seminars in Cancer …, 2023 - Elsevier
Head and neck tumors (HNTs) constitute a multifaceted ensemble of pathologies that
primarily involve regions such as the oral cavity, pharynx, and nasal cavity. The intricate …
primarily involve regions such as the oral cavity, pharynx, and nasal cavity. The intricate …
Segment anything model for medical images?
Abstract The Segment Anything Model (SAM) is the first foundation model for general image
segmentation. It has achieved impressive results on various natural image segmentation …
segmentation. It has achieved impressive results on various natural image segmentation …
Clip-driven universal model for organ segmentation and tumor detection
An increasing number of public datasets have shown a marked impact on automated organ
segmentation and tumor detection. However, due to the small size and partially labeled …
segmentation and tumor detection. However, due to the small size and partially labeled …
One model to rule them all: Towards universal segmentation for medical images with text prompts
In this study, we focus on building up a model that can Segment Anything in medical
scenarios, driven by Text prompts, termed as SAT. Our main contributions are three folds:(i) …
scenarios, driven by Text prompts, termed as SAT. Our main contributions are three folds:(i) …
Context-aware meta-learning
Large Language Models like ChatGPT demonstrate a remarkable capacity to learn new
concepts during inference without any fine-tuning. However, visual models trained to detect …
concepts during inference without any fine-tuning. However, visual models trained to detect …
WHRIME: A weight-based recursive hierarchical RIME optimizer for breast cancer histopathology image segmentation
J Xing, AA Heidari, H Chen, H Zhao - Displays, 2024 - Elsevier
In medical image processing, multi-threshold image segmentation has been challenging, as
selecting appropriate thresholds is crucial for distinguishing different structures within an …
selecting appropriate thresholds is crucial for distinguishing different structures within an …
Dual-reference source-free active domain adaptation for nasopharyngeal carcinoma tumor segmentation across multiple hospitals
H Wang, J Chen, S Zhang, Y He, J Xu… - … on Medical Imaging, 2024 - ieeexplore.ieee.org
Nasopharyngeal carcinoma (NPC) is a prevalent and clinically significant malignancy that
predominantly impacts the head and neck area. Precise delineation of the Gross Tumor …
predominantly impacts the head and neck area. Precise delineation of the Gross Tumor …
BAFNet: Bottleneck attention based fusion network for sleep apnea detection
Sleep apnea (SA) is a common sleep-related breathing disorder that tends to induce a
series of complications, such as pediatric intracranial hypertension, psoriasis, and even …
series of complications, such as pediatric intracranial hypertension, psoriasis, and even …
Neuralizer: General Neuroimage Analysis without Re-Training
Neuroimage processing tasks like segmentation, reconstruction, and registration are central
to the study of neuroscience. Robust deep learning strategies and architectures used to …
to the study of neuroscience. Robust deep learning strategies and architectures used to …