Zobrazeno 1 - 10
of 717
pro vyhledávání: '"Lachinov, A. A."'
Autor:
Emre, Taha, Chakravarty, Arunava, Lachinov, Dmitrii, Rivail, Antoine, Schmidt-Erfurth, Ursula, Bogunović, Hrvoje
Contrastive pretraining provides robust representations by ensuring their invariance to different image transformations while simultaneously preventing representational collapse. Equivariant contrastive learning, on the other hand, provides represent
Externí odkaz:
http://arxiv.org/abs/2405.09404
Autor:
Emre, Taha, Chakravarty, Arunava, Rivail, Antoine, Lachinov, Dmitrii, Leingang, Oliver, Riedl, Sophie, Mai, Julia, Scholl, Hendrik P. N., Sivaprasad, Sobha, Rueckert, Daniel, Lotery, Andrew, Schmidt-Erfurth, Ursula, Bogunović, Hrvoje
Self-supervised learning (SSL) has emerged as a powerful technique for improving the efficiency and effectiveness of deep learning models. Contrastive methods are a prominent family of SSL that extract similar representations of two augmented views o
Externí odkaz:
http://arxiv.org/abs/2312.16980
The Segment Anything Model (SAM) has gained significant attention in the field of image segmentation due to its impressive capabilities and prompt-based interface. While SAM has already been extensively evaluated in various domains, its adaptation to
Externí odkaz:
http://arxiv.org/abs/2308.09331
Autor:
Morano, José, Aresta, Guilherme, Lachinov, Dmitrii, Mai, Julia, Schmidt-Erfurth, Ursula, Bogunović, Hrvoje
Deep learning has become a valuable tool for the automation of certain medical image segmentation tasks, significantly relieving the workload of medical specialists. Some of these tasks require segmentation to be performed on a subset of the input di
Externí odkaz:
http://arxiv.org/abs/2307.03008
Autor:
Lachinov, Dmitrii, Chakravarty, Arunava, Grechenig, Christoph, Schmidt-Erfurth, Ursula, Bogunovic, Hrvoje
Robust forecasting of the future anatomical changes inflicted by an ongoing disease is an extremely challenging task that is out of grasp even for experienced healthcare professionals. Such a capability, however, is of great importance since it can i
Externí odkaz:
http://arxiv.org/abs/2211.04234
Autor:
Fazekas, Botond, Lachinov, Dmitrii, Aresta, Guilherme, Mai, Julia, Schmidt-Erfurth, Ursula, Bogunovic, Hrvoje
Bruch's membrane (BM) segmentation on optical coherence tomography (OCT) is a pivotal step for the diagnosis and follow-up of age-related macular degeneration (AMD), one of the leading causes of blindness in the developed world. Automated BM segmenta
Externí odkaz:
http://arxiv.org/abs/2210.14799
Autor:
Fazekas, Botond, Aresta, Guilherme, Lachinov, Dmitrii, Riedl, Sophie, Mai, Julia, Schmidt-Erfurth, Ursula, Bogunovic, Hrvoje
Publikováno v:
MICCAI 2022. Lecture Notes in Computer Science, vol 13438. Springer, Cham
Optical coherence tomography (OCT) is a non-invasive 3D modality widely used in ophthalmology for imaging the retina. Achieving automated, anatomically coherent retinal layer segmentation on OCT is important for the detection and monitoring of differ
Externí odkaz:
http://arxiv.org/abs/2207.00458
Autor:
Mai, Julia, Lachinov, Dmitrii, Reiter, Gregor S., Riedl, Sophie, Grechenig, Christoph, Bogunovic, Hrvoje, Schmidt-Erfurth, Ursula
Publikováno v:
In Ophthalmology Science July-August 2024 4(4)
In medical imaging, there are clinically relevant segmentation tasks where the output mask is a projection to a subset of input image dimensions. In this work, we propose a novel convolutional neural network architecture that can effectively learn to
Externí odkaz:
http://arxiv.org/abs/2108.00831
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