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Found 8 papers, 1 papers with code
Self-distillation for surgical action recognition
Surgical scene understanding is a key prerequisite for contextaware decision support in the operating room.
Unsupervised Domain Transfer with Conditional Invertible Neural Networks
Synthetic medical image generation has evolved as a key technique for neural network training and validation.
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)
Semantic segmentation of multispectral photoacoustic images using deep learning
Due to the intuitive representation of high-dimensional information, such a preprocessing algorithm could be a valuable means to facilitate the clinical translation of photoacoustic imaging.
Photoacoustic image synthesis with generative adversarial networks
Photoacoustic tomography (PAT) has the potential to recover morphological and functional tissue properties with high spatial resolution.
Tattoo tomography: Freehand 3D photoacoustic image reconstruction with an optical pattern
Methods: In this paper, we present a novel approach to 3D reconstruction of PAT data (Tattoo tomography) that does not require an external tracking system and can smoothly be integrated into clinical workflows.
Deep learning for biomedical photoacoustic imaging: A review
Photoacoustic imaging (PAI) is a promising emerging imaging modality that enables spatially resolved imaging of optical tissue properties up to several centimeters deep in tissue, creating the potential for numerous exciting clinical applications.
Heidelberg Colorectal Data Set for Surgical Data Science in the Sensor Operating Room
Image-based tracking of medical instruments is an integral part of surgical data science applications.
