output
20172026
most citedGesture Recognition in Robotic Surgery: a Review

158 citations

Showing 2021Show all

9 papers · 1 filter

eess.IV2021

Real-time multimodal image registration with partial intraoperative point-set data

Zachary M C Baum, Yipeng Hu, Dean C Barratt

We present Free Point Transformer (FPT) - a deep neural network architecture for non-rigid point-set registration. Consisting of two modules, a global feature extraction module and…

cs.CV2021

Adaptable image quality assessment using meta-reinforcement learning of task amenability

Shaheer U. Saeed, Yunguan Fu, Vasilis Stavrinides +8

The performance of many medical image analysis tasks are strongly associated with image data quality. When developing modern deep learning algorithms, rather than relying on subjec…

eess.IV2021

Controlling False Positive/Negative Rates for Deep-Learning-Based Prostate Cancer Detection on Multiparametric MR images

Zhe Min, Fernando J. Bianco, Qianye Yang +4

Prostate cancer (PCa) is one of the leading causes of death for men worldwide. Multi-parametric magnetic resonance (mpMR) imaging has emerged as a non-invasive diagnostic tool for…

cs.CV202121 cited

Transfer Learning of Deep Spatiotemporal Networks to Model Arbitrarily Long Videos of Seizures

Fernando Pérez-García, Catherine Scott, Rachel Sparks +2

Detailed analysis of seizure semiology, the symptoms and signs which occur during a seizure, is critical for management of epilepsy patients. Inter-rater reliability using qualitat…

eess.IV202132 cited

A self-supervised learning strategy for postoperative brain cavity segmentation simulating resections

Fernando Pérez-García, Reuben Dorent, Michele Rizzi +9

Accurate segmentation of brain resection cavities (RCs) aids in postoperative analysis and determining follow-up treatment. Convolutional neural networks (CNNs) are the state-of-th…

eess.IV202117 cited

Zero-shot super-resolution with a physically-motivated downsampling kernel for endomicroscopy

Agnieszka Barbara Szczotka, Dzhoshkun Ismail Shakir, Matthew J. Clarkson +2

Super-resolution (SR) methods have seen significant advances thanks to the development of convolutional neural networks (CNNs). CNNs have been successfully employed to improve the…