activity
20182021
most citedAdversarial training with cycle consistency for unsupervised super-resolution in endomicroscopy

68 citations · 85 across the 2 of their papers we have counts for

collaborators

4 papers

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…

eess.IV2019

Learning from Irregularly Sampled Data for Endomicroscopy Super-resolution: A Comparative Study of Sparse and Dense Approaches

Agnieszka Barbara Szczotka, Dzhoshkun Ismail Shakir, DanieleRavi +3

Purpose: Probe-based Confocal Laser Endomicroscopy (pCLE) enables performing an optical biopsy, providing real-time microscopic images, via a probe. pCLE probes consist of multiple…

cs.CV201968 cited

Adversarial training with cycle consistency for unsupervised super-resolution in endomicroscopy

Daniele Ravì, Agnieszka Barbara Szczotka, Stephen P Pereira +1

In recent years, endomicroscopy has become increasingly used for diagnostic purposes and interventional guidance. It can provide intraoperative aids for real-time tissue characteri…

cs.CV2018

Effective deep learning training for single-image super-resolution in endomicroscopy exploiting video-registration-based reconstruction

Daniele Ravì, Agnieszka Barbara Szczotka, Dzhoshkun Ismail Shakir +2

Purpose: Probe-based Confocal Laser Endomicroscopy (pCLE) is a recent imaging modality that allows performing in vivo optical biopsies. The design of pCLE hardware, and its relianc…