7 papers
Colon-X: Advancing Intelligent Colonoscopy toward Clinical Reasoning
Ge-Peng Ji, Jingyi Liu, Deng-Ping Fan +2
In this study, we present Colon-X, an open initiative aimed at advancing multimodal intelligence in colonoscopy. We begin by constructing ColonVQA, the most comprehensive multimoda…
PraNet-V2: Dual-Supervised Reverse Attention for Medical Image Segmentation
Bo-Cheng Hu, Ge-Peng Ji, Dian Shao +1
Accurate medical image segmentation is essential for effective diagnosis and treatment. Previously, PraNet-V1 was proposed to enhance polyp segmentation by introducing a reverse at…
LawDIS: Language-Window-based Controllable Dichotomous Image Segmentation
Xinyu Yan, Meijun Sun, Ge-Peng Ji +3
We present LawDIS, a language-window-based controllable dichotomous image segmentation (DIS) framework that produces high-quality object masks. Our framework recasts DIS as an imag…
Deep Learning in Concealed Dense Prediction
Pancheng Zhao, Deng-Ping Fan, Shupeng Cheng +5
Deep learning is developing rapidly and handling common computer vision tasks well. It is time to pay attention to more complex vision tasks, as model size, knowledge, and reasonin…
Frontiers in Intelligent Colonoscopy
Ge-Peng Ji, Jingyi Liu, Peng Xu +4
Colonoscopy is currently one of the most sensitive screening methods for colorectal cancer. This study investigates the frontiers of intelligent colonoscopy techniques and their pr…
Effectiveness Assessment of Recent Large Vision-Language Models
Yao Jiang, Xinyu Yan, Ge-Peng Ji +5
The advent of large vision-language models (LVLMs) represents a remarkable advance in the quest for artificial general intelligence. However, the model's effectiveness in both spec…