研究论文
MadCLIP: Few-Shot Medical Anomaly Detection with CLIP
Mahshid Shiri, Cigdem Beyan, Vittorio Murino
University of Verona Italian Institute of Technology
来源Lecture notes in computer science
年份2025
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生物医学COVID-19 diagnosis using AI
Anomaly Detection Techniques and Applications · Data-Driven Disease Surveillance
参考文献 32
The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)
被引 6,736Bjoern Menze, András Jakab, Stefan Bauer · IEEE Transactions on Medical Imaging · 2014
The Alzheimer's disease neuroimaging initiative (ADNI): MRI methods
被引 4,448Clifford R. Jack, Matt A. Bernstein, Nick C. Fox · Journal of Magnetic Resonance Imaging · 2008
ChestX-Ray8: Hospital-Scale Chest X-Ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases
被引 3,427Xiaosong Wang, Yifan Peng, Le Lu · 2017
此处列出前 3 条
引用本文 3
GF-few: a real-time lightweight Gaussian feature enhanced few-shot network for industrial defect detection
被引 0Q. Ma, Erhu Zhang, Yajun Chen · Journal of Real-Time Image Processing · 2025
HAC: Parameter-Efficient Hyperbolic Adaptation of CLIP for Zero-Shot VQA
被引 0Francesco Dibitonto, Cigdem Beyan, Vittorio Murino · Lecture notes in computer science · 2026
Unsupervised Anomaly Detection in Medical Imaging: A Survey of Methods, Challenges, and Future Directions
被引 0Boyang Liu, Guangli Li, Yuxing Zou · Bioengineering · 2026
按被引量排序,此处列出前 3 条