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Found 12 papers, 6 papers with code
OphCLIP: Hierarchical Retrieval-Augmented Learning for Ophthalmic Surgical Video-Language Pretraining
Surgical practice involves complex visual interpretation, procedural skills, and advanced medical knowledge, making surgical vision-language pretraining (VLP) particularly challenging due to this complexity and the limited availability of annotated data.
A General-Purpose Multimodal Foundation Model for Dermatology
Here, we introduce PanDerm, a multimodal dermatology foundation model pretrained through self-supervised learning on a dataset of over 2 million real-world images of skin diseases, sourced from 11 clinical institutions across 4 imaging modalities.
MONICA: Benchmarking on Long-tailed Medical Image Classification
We hope this codebase serves as a comprehensive and reproducible benchmark, encouraging further advancements in long-tailed medical image learning.
OphNet: A Large-Scale Video Benchmark for Ophthalmic Surgical Workflow Understanding
With approximately 285 hours of surgical videos, OphNet is about 20 times larger than the largest existing surgical workflow analysis benchmark.
Diffusion Model Driven Test-Time Image Adaptation for Robust Skin Lesion Classification
In this paper, we propose a test-time image adaptation method to enhance the accuracy of the model on test data by simultaneously updating and predicting test images.
Enhancing Vision-Language Models Generalization via Diversity-Driven Novel Feature Synthesis
To address this, we propose a plug-and-play feature synthesis method called LDFS (Language-Guided Diverse Feature Synthesis) to synthesize new domain features and improve existing CLIP fine-tuning strategies.
Prompt-driven Latent Domain Generalization for Medical Image Classification
To address these challenges, we propose a novel DG framework for medical image classification without relying on domain labels, called Prompt-driven Latent Domain Generalization (PLDG).
EPVT: Environment-aware Prompt Vision Transformer for Domain Generalization in Skin Lesion Recognition
Concretely, EPVT leverages a set of domain prompts, each of which plays as a domain expert, to capture domain-specific knowledge; and a shared prompt for general knowledge over the entire dataset.
Transmission-Guided Bayesian Generative Model for Smoke Segmentation
To effectively model the two types of uncertainty, we introduce a Bayesian generative model to simultaneously estimate the posterior distribution of model parameters and its predictions.
Towards Trustable Skin Cancer Diagnosis via Rewriting Model's Decision
We introduce a human-in-the-loop framework in the model training process such that users can observe and correct the model's decision logic when confounding behaviors happen.
An overlapping-free leaf segmentation method for plant point clouds
The proposed method can also facilitate the automatic traits estimation of each single leaf (such as the leaf area, length, and width), which has potential to become a highly effective tool for plant research and agricultural engineering.
An Integrated Image Filter for Enhancing Change Detection Results
In this paper, we present an integrated filter which comprises a weighted local guided image filter and a weighted spatiotemporal tree filter.
