Application of artificial intelligence in surgery
Artificial intelligence (AI) is gradually changing the practice of surgery with technological
advancements in imaging, navigation, and robotic intervention. In this article, we review the …
advancements in imaging, navigation, and robotic intervention. In this article, we review the …
Deep learning in cardiology
P Bizopoulos, D Koutsouris - IEEE reviews in biomedical …, 2018 - ieeexplore.ieee.org
The medical field is creating large amount of data that physicians are unable to decipher
and use efficiently. Moreover, rule-based expert systems are inefficient in solving …
and use efficiently. Moreover, rule-based expert systems are inefficient in solving …
Synthetic data accelerates the development of generalizable learning-based algorithms for X-ray image analysis
Artificial intelligence (AI) now enables automated interpretation of medical images. However,
AI's potential use for interventional image analysis remains largely untapped. This is …
AI's potential use for interventional image analysis remains largely untapped. This is …
Deep adversarial training for multi-organ nuclei segmentation in histopathology images
Nuclei mymargin segmentation is a fundamental task for various computational pathology
applications including nuclei morphology analysis, cell type classification, and cancer …
applications including nuclei morphology analysis, cell type classification, and cancer …
EndoSLAM dataset and an unsupervised monocular visual odometry and depth estimation approach for endoscopic videos
Deep learning techniques hold promise to develop dense topography reconstruction and
pose estimation methods for endoscopic videos. However, currently available datasets do …
pose estimation methods for endoscopic videos. However, currently available datasets do …
Unsupervised reverse domain adaptation for synthetic medical images via adversarial training
To realize the full potential of deep learning for medical imaging, large annotated datasets
are required for training. Such datasets are difficult to acquire due to privacy issues, lack of …
are required for training. Such datasets are difficult to acquire due to privacy issues, lack of …
Self-supervised monocular depth and ego-motion estimation in endoscopy: Appearance flow to the rescue
Recently, self-supervised learning technology has been applied to calculate depth and ego-
motion from monocular videos, achieving remarkable performance in autonomous driving …
motion from monocular videos, achieving remarkable performance in autonomous driving …
Domain adaptive deep belief network for rolling bearing fault diagnosis
C Che, H Wang, X Ni, Q Fu - Computers & Industrial Engineering, 2020 - Elsevier
As the essential components of rotating machines, rolling bearings always operate in
variable working conditions and suffer from different failure modes. To address the issue of …
variable working conditions and suffer from different failure modes. To address the issue of …
Colonoscopy 3D video dataset with paired depth from 2D-3D registration
Screening colonoscopy is an important clinical application for several 3D computer vision
techniques, including depth estimation, surface reconstruction, and missing region …
techniques, including depth estimation, surface reconstruction, and missing region …
Implicit domain adaptation with conditional generative adversarial networks for depth prediction in endoscopy
Purpose Colorectal cancer is the third most common cancer worldwide, and early
therapeutic treatment of precancerous tissue during colonoscopy is crucial for better …
therapeutic treatment of precancerous tissue during colonoscopy is crucial for better …