Zobrazeno 1 - 10
of 2 281
pro vyhledávání: '"Herrera, Luis A"'
Autor:
Ghaiedi, Homa, Herrera, Luis Carlos Pinzon, Alshafeay, Saja, Harris, Leonard, Almodovar, Jorge, Nayani, Karthik
Collagen is a key component of the extracellular matrix and well-oriented domains of collagen are relevant for mimicking the local cell environment in vitro. While there has been significant attention directed towards the alignment of collagen, forma
Externí odkaz:
http://arxiv.org/abs/2405.02948
Deep neural networks for medical image segmentation often produce overconfident results misaligned with empirical observations. Such miscalibration, challenges their clinical translation. We propose to use marginal L1 average calibration error (mL1-A
Externí odkaz:
http://arxiv.org/abs/2403.06759
Autor:
Wei, Meng, Budd, Charlie, Garcia-Peraza-Herrera, Luis C., Dorent, Reuben, Shi, Miaojing, Vercauteren, Tom
Surgical instrument segmentation is recognised as a key enabler to provide advanced surgical assistance and improve computer assisted interventions. In this work, we propose SegMatch, a semi supervised learning method to reduce the need for expensive
Externí odkaz:
http://arxiv.org/abs/2308.05232
Autor:
Liu, Yang, Boels, Maxence, Garcia-Peraza-Herrera, Luis C., Vercauteren, Tom, Dasgupta, Prokar, Granados, Alejandro, Ourselin, Sebastien
Online surgical phase recognition plays a significant role towards building contextual tools that could quantify performance and oversee the execution of surgical workflows. Current approaches are limited since they train spatial feature extractors u
Externí odkaz:
http://arxiv.org/abs/2305.08989
Autor:
Garcia-Peraza-Herrera, Luis C., Horgan, Conor, Ourselin, Sebastien, Ebner, Michael, Vercauteren, Tom
Visual discrimination of clinical tissue types remains challenging, with traditional RGB imaging providing limited contrast for such tasks. Hyperspectral imaging (HSI) is a promising technology providing rich spectral information that can extend far
Externí odkaz:
http://arxiv.org/abs/2303.08252
The performance of deep learning (DL) algorithms is heavily influenced by the quantity and the quality of the annotated data. However, in Surgical Data Science, access to it is limited. It is thus unsurprising that substantial research efforts are ma
Externí odkaz:
http://arxiv.org/abs/2303.10173
Autor:
Schneider, Marc, Herrera, Luis Alberto Garcia, Burger, Birgit, Eisenblätter, Lars, Kühner, Thomas
We report on our latest developments of a planar fiber-chip-coupling scheme, using angle polished, polarization maintaining (PM) fibers. Most integrated photonic chip components are polarization sensitive and a suitable way to launch several waveleng
Externí odkaz:
http://arxiv.org/abs/2301.04927
Autor:
Budd, Charlie, Garcia-Peraza-Herrera, Luis C., Huber, Martin, Ourselin, Sebastien, Vercauteren, Tom
Endoscopic content area refers to the informative area enclosed by the dark, non-informative, border regions present in most endoscopic footage. The estimation of the content area is a common task in endoscopic image processing and computer vision pi
Externí odkaz:
http://arxiv.org/abs/2210.14771
The paper investigates the problems of quickest change detection in Markov models and hidden Markov models (HMMs). Sequential observations are taken from a (hidden) Markov model. At some unknown time, an event occurs in the system and changes the tra
Externí odkaz:
http://arxiv.org/abs/2210.11988
Autor:
Guillén Perales, Alberto, Liébana-Cabanillas, Francisco, Sánchez-Fernández, Juan, Herrera, Luis Javier
Publikováno v:
Applied Computing and Informatics, 2020, Vol. 20, Issue 1/2, pp. 20-34.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/ACI-06-2020-0003