Zobrazeno 1 - 10
of 44
pro vyhledávání: '"Nick Pawlowski"'
Autor:
Martin J. Menten, PhD, Robbie Holland, MSc, Oliver Leingang, PhD, Hrvoje Bogunović, PhD, Ahmed M. Hagag, MD, Rebecca Kaye, MD, Sophie Riedl, MD, Ghislaine L. Traber, MD, Osama N. Hassan, MSc, Nick Pawlowski, PhD, Ben Glocker, PhD, Lars G. Fritsche, PhD, Hendrik P.N. Scholl, MD, Sobha Sivaprasad, MD, Ursula Schmidt-Erfurth, MD, Daniel Rueckert, PhD, Andrew J. Lotery, MD
Publikováno v:
Ophthalmology Science, Vol 3, Iss 3, Pp 100294- (2023)
Purpose: To study the individual course of retinal changes caused by healthy aging using deep learning. Design: Retrospective analysis of a large data set of retinal OCT images. Participants: A total of 85 709 adults between the age of 40 and 75 year
Externí odkaz:
https://doaj.org/article/e0eb53ffa5f04287a5154c4856cf8732
Autor:
Martin J. Menten, Robbie Holland, Oliver Leingang, Hrvoje Bogunović, Ahmed M. Hagag, Rebecca Kaye, Sophie Riedl, Ghislaine L. Traber, Osama N. Hassan, Nick Pawlowski, Ben Glocker, Lars G. Fritsche, Hendrik P.N. Scholl, Sobha Sivaprasad, Ursula Schmidt-Erfurth, Daniel Rueckert, Andrew J. Lotery
PurposeTo study the individual course of retinal changes caused by healthy aging using deep learning.DesignRetrospective analysis of a large dataset of retinal optical coherence tomography (OCT) images.ParticipantsEighty-five thousand seven hundred a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::783c8202551081ac200149d12bd95b02
https://eprints.soton.ac.uk/476645/
https://eprints.soton.ac.uk/476645/
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031250743
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dbc63da2b6f47558c9a4d4e8635a8cc1
https://doi.org/10.1007/978-3-031-25075-0_28
https://doi.org/10.1007/978-3-031-25075-0_28
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 30:3409-3418
One of the main concerns of deep reinforcement learning (DRL) is the data inefficiency problem, which stems both from an inability to fully utilize data acquired and from naive exploration strategies. In order to alleviate these problems, we propose
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d0b7111498b381c5153f67377dec0b7
https://doi.org/10.1109/tnnls.2019.2891792
https://doi.org/10.1109/tnnls.2019.2891792
Publikováno v:
Smart Ultrasound Imaging and Perinatal, Preterm and Paediatric Image Analysis ISBN: 9783030328740
SUSI/PIPPI@MICCAI
Smart Ultrasound Imaging and Perinatal, Preterm and Paediatric Image Analysis
SUSI/PIPPI@MICCAI
Smart Ultrasound Imaging and Perinatal, Preterm and Paediatric Image Analysis
One of the biggest challenges for deep learning algorithms in medical image analysis is the indiscriminate mixing of image properties, e.g. artifacts and anatomy. These entangled image properties lead to a semantically redundant feature encoding for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0d96948f487311588325474853c8f912
http://arxiv.org/abs/1908.07885
http://arxiv.org/abs/1908.07885
Publikováno v:
Machine Learning in Medical Imaging ISBN: 9783030326913
MLMI@MICCAI
MLMI@MICCAI
Generative models have recently been applied to unsupervised lesion detection, where a distribution of normal data, i.e. the normative distribution, is learned and lesions are detected as out-of-distribu-tion regions. However, directly calculating th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5fed44dfb7ae5f1cbc457d0a27be2b4e
https://doi.org/10.1007/978-3-030-32692-0_41
https://doi.org/10.1007/978-3-030-32692-0_41
Autor:
Daniel Rueckert, Martin Rajchl, Ben Glocker, Ioannis Lavdas, Vanya V. Valindria, Nick Pawlowski, Andrea Rockall, Eric O. Aboagye
Publikováno v:
IEEE Winter Conference on Applications of Computer Vision
WACV
WACV
Convolutional neural networks have been widely used in medical image segmentation. The amount of training data strongly determines the overall performance. Most approaches are applied for a single imaging modality, e.g., brain MRI. In practice, it is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2bc3a7f9820296735099135c77a011d3
http://hdl.handle.net/10044/1/56452
http://hdl.handle.net/10044/1/56452
Autor:
Matthew C. H. Lee, Bernhard Kainz, Steven McDonagh, Enzo Ferrante, Matthew Sinclair, Martin Rajchl, Daniel Rueckert, Konstantinos Kamnitsas, Wenjia Bai, Ben Glocker, Nick Pawlowski
Publikováno v:
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries ISBN: 9783319752372
BrainLes@MICCAI
MICCAI BrainLes Workshop
BrainLes@MICCAI
MICCAI BrainLes Workshop
Deep learning approaches such as convolutional neural nets have consistently outperformed previous methods on challenging tasks such as dense, semantic segmentation. However, the various proposed networks perform differently, with behaviour largely i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::422b7a7d80e2f8da0e7540b2b49f1bcf
http://hdl.handle.net/10044/1/54498
http://hdl.handle.net/10044/1/54498
We explore the application of Generative Adversarial Networks to the domain of morphological profiling of human cultured cells imaged by fluorescence microscopy. When evaluated for their ability to group cell images responding to treatment by chemica
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::efe57de6f91202b8ebbdd27586a2ce0d
Autor:
Liu, Yanbin1 (AUTHOR) csyanbin@gmail.com, Dwivedi, Girish2 (AUTHOR) girish.dwivedi@perkins.uwa.edu.au, Boussaid, Farid3 (AUTHOR) farid.boussaid@uwa.edu.au, Bennamoun, Mohammed4 (AUTHOR) mohammed.bennamoun@uwa.edu.au
Publikováno v:
ACM Computing Surveys. Jun2024, Vol. 56 Issue 6, p1-37. 37p.