Search Results
CPPE-5: Medical Personal Protective Equipment Dataset
The image collection for this dataset focuses on: obtaining as many non-iconic images as possible and making sure all the images are real-life images, unlike other existing datasets in this area.
Ranked #1 on
Object Detection
on CPPE-5
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
Implementation of different kinds of Unet Models for Image Segmentation - Unet , RCNN-Unet, Attention Unet, RCNN-Attention Unet, Nested Unet
Ranked #1 on
Video Polyp Segmentation
on SUN-SEG-Easy
TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation
Medical image segmentation is an essential prerequisite for developing healthcare systems, especially for disease diagnosis and treatment planning.
Ranked #4 on
Medical Image Segmentation
on ACDC
nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation
The U-Net was presented in 2015.
Ranked #2 on
Medical Image Segmentation
on Synapse multi-organ CT
nnU-Net Revisited: A Call for Rigorous Validation in 3D Medical Image Segmentation
The release of nnU-Net marked a paradigm shift in 3D medical image segmentation, demonstrating that a properly configured U-Net architecture could still achieve state-of-the-art results.
HuaTuo: Tuning LLaMA Model with Chinese Medical Knowledge
Large Language Models (LLMs), such as the LLaMA model, have demonstrated their effectiveness in various general-domain natural language processing (NLP) tasks.
Cutting-edge 3D Medical Image Segmentation Methods in 2020: Are Happy Families All Alike?
Segmentation is one of the most important and popular tasks in medical image analysis, which plays a critical role in disease diagnosis, surgical planning, and prognosis evaluation.
ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledge
The primary aim of this research was to address the limitations observed in the medical knowledge of prevalent large language models (LLMs) such as ChatGPT, by creating a specialized language model with enhanced accuracy in medical advice.
Querying Across Genres for Medical Claims in News
We present a query-based biomedical information retrieval task across two vastly different genres {--} newswire and research literature {--} where the goal is to find the research publication that supports the primary claim made in a health-related news article.
UNETR: Transformers for 3D Medical Image Segmentation
Inspired by the recent success of transformers for Natural Language Processing (NLP) in long-range sequence learning, we reformulate the task of volumetric (3D) medical image segmentation as a sequence-to-sequence prediction problem.
