Towards an efficient way of building annotated medical image collections for big data studies
Annotating large collections of medical images is essential for building robust image
analysis pipelines for different applications, such as disease detection. This process …
analysis pipelines for different applications, such as disease detection. This process …
Position statement on priorities for artificial intelligence in GI endoscopy: a report by the ASGE Task Force
Artificial intelligence (AI) in GI endoscopy holds tremendous promise to augment clinical
performance, establish better treatment plans, and improve patient outcomes. Although …
performance, establish better treatment plans, and improve patient outcomes. Although …
Deep learning and convolutional neural networks for medical image computing
This book was partially motivated by the recent rapid progress on deep convolutional and
recurrent neural network models and the abundance of important applications in computer …
recurrent neural network models and the abundance of important applications in computer …
[PDF][PDF] Endoscopic computer vision challenges 2.0.
S Ali, NM Ghatwary - EndoCV@ ISBI, 2022 - ceur-ws.org
Accurate detection of artefacts is a core challenge in a wide-range of endoscopic
applications addressing multiple different disease areas. The importance of precise …
applications addressing multiple different disease areas. The importance of precise …
[HTML][HTML] Accelerating voxelwise annotation of cross-sectional imaging through AI collaborative labeling with quality assurance and bias mitigation
Background precision-medicine quantitative tools for cross-sectional imaging require
painstaking labeling of targets that vary considerably in volume, prohibiting scaling of data …
painstaking labeling of targets that vary considerably in volume, prohibiting scaling of data …
Bimodal network architectures for automatic generation of image annotation from text
Medical image analysis practitioners have embraced big data methodologies. This has
created a need for large annotated datasets. The source of big data is typically large image …
created a need for large annotated datasets. The source of big data is typically large image …
SEGCROP: Segmentation-based dynamic cropping of endoscopic videos to address label leakage in surgical tool detection
In recent times, surgical data science has emerged as an important research discipline in
interventional healthcare. There are many potential applications for analysing endoscopic …
interventional healthcare. There are many potential applications for analysing endoscopic …
STIR: Surgical Tattoos in Infrared
A Schmidt, O Mohareri, S DiMaio… - arXiv preprint arXiv …, 2023 - arxiv.org
Quantifying performance of methods for tracking and mapping tissue in endoscopic
environments is essential for enabling image guidance and automation of medical …
environments is essential for enabling image guidance and automation of medical …
Depth information-based automatic annotation of early esophageal cancers in gastroscopic images using deep learning techniques
D Liu, H Jiang, N Rao, W Du, C Luo, Z Li, L Zhu… - IEEE …, 2020 - ieeexplore.ieee.org
The early diagnoses of esophageal cancer are of great significance in the clinic because
they are critical for reducing mortality. At present, the diagnoses are mainly performed by …
they are critical for reducing mortality. At present, the diagnoses are mainly performed by …
[HTML][HTML] Kvasir-Capsule, a video capsule endoscopy dataset
Artificial intelligence (AI) is predicted to have profound effects on the future of video capsule
endoscopy (VCE) technology. The potential lies in improving anomaly detection while …
endoscopy (VCE) technology. The potential lies in improving anomaly detection while …