2 citations · 2 across the 5 of their papers we have counts for
5 papers
Vision-Language Models for Automated 3D PET/CT Report Generation
Wenpei Jiao, Kun Shang, Hui Li +8
Positron emission tomography/computed tomography (PET/CT) is essential in oncology, yet the rapid expansion of scanners has outpaced the availability of trained specialists, making…
Inter- and Intra-image Refinement for Few Shot Segmentation
Ourui Fu, Hangzhou He, Kaiwen Li +5
Deep neural networks for semantic segmentation rely on large-scale annotated datasets, leading to an annotation bottleneck that motivates few shot semantic segmentation (FSS) which…
Don't Fear Peculiar Activation Functions: EUAF and Beyond
Qianchao Wang, Shijun Zhang, Dong Zeng +4
In this paper, we propose a new super-expressive activation function called the Parametric Elementary Universal Activation Function (PEUAF). We demonstrate the effectiveness of PEU…
FP-PET: Large Model, Multiple Loss And Focused Practice
Yixin Chen, Ourui Fu, Wenrui Shao +1
This study presents FP-PET, a comprehensive approach to medical image segmentation with a focus on CT and PET images. Utilizing a dataset from the AutoPet2023 Challenge, the resear…
Multi-level Asymmetric Contrastive Learning for Volumetric Medical Image Segmentation Pre-training
Shuang Zeng, Lei Zhu, Xinliang Zhang +10
Medical image segmentation is a fundamental yet challenging task due to the arduous process of acquiring large volumes of high-quality labeled data from experts. Contrastive learni…