Search Results for author:
Found 11 papers, 6 papers with code
ORacle: Large Vision-Language Models for Knowledge-Guided Holistic OR Domain Modeling
This demonstrates ORacle's potential to significantly enhance the scalability and affordability of OR domain modeling and opens a pathway for future advancements in surgical data science.
Ranked #1 on
Scene Graph Generation
on 4D-OR
RaDialog: A Large Vision-Language Model for Radiology Report Generation and Conversational Assistance
Conversational AI tools that can generate and discuss clinically correct radiology reports for a given medical image have the potential to transform radiology.
Dynamic Scene Graph Representation for Surgical Video
Surgical videos captured from microscopic or endoscopic imaging devices are rich but complex sources of information, depicting different tools and anatomical structures utilized during an extended amount of time.
Rad-ReStruct: A Novel VQA Benchmark and Method for Structured Radiology Reporting
However, there is limited research on automating structured reporting, and no public benchmark is available for evaluating and comparing different methods.
Ranked #1 on
Structured Report Generation
on Rad-ReStruct
Whether and When does Endoscopy Domain Pretraining Make Sense?
In this work, we investigate the need for endoscopy domain-specific pretraining based on downstream objectives.
Xplainer: From X-Ray Observations to Explainable Zero-Shot Diagnosis
Automated diagnosis prediction from medical images is a valuable resource to support clinical decision-making.
LABRAD-OR: Lightweight Memory Scene Graphs for Accurate Bimodal Reasoning in Dynamic Operating Rooms
The holistic representation of surgical scenes as semantic scene graphs (SGG), where entities are represented as nodes and relations between them as edges, is a promising direction for fine-grained semantic OR understanding.
Ranked #3 on
Scene Graph Generation
on 4D-OR
Location-Free Scene Graph Generation
Although using significantly fewer labels during training, we achieve 74. 12\% of the location-supervised SOTA performance on Visual Genome and even outperform the best method on 4D-OR.
Ranked #2 on
Scene Graph Generation
on 4D-OR
CholecTriplet2022: Show me a tool and tell me the triplet -- an endoscopic vision challenge for surgical action triplet detection
This paper presents the CholecTriplet2022 challenge, which extends surgical action triplet modeling from recognition to detection.
Ranked #1 on
Action Triplet Detection
on CholecT50 (Challenge)
4D-OR: Semantic Scene Graphs for OR Domain Modeling
Towards this goal, for the first time, we propose using semantic scene graphs (SSG) to describe and summarize the surgical scene.
Ranked #4 on
Scene Graph Generation
on 4D-OR
Multimodal Semantic Scene Graphs for Holistic Modeling of Surgical Procedures
We then use MSSG to introduce a dynamically generated graphical user interface tool for surgical procedure analysis which could be used for many applications including process optimization, OR design and automatic report generation.
