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Dmitry A. Lachinov
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2020 – today
- 2024
- [j5]Dmitrii A. Lachinov
, Arunava Chakravarty
Learning Spatio-Temporal Model of Disease Progression With NeuralODEs From Longitudinal Volumetric Data. IEEE Trans. Medical Imaging 43(3): 1165-1179 (2024) - [j4]Taha Emre
3DTINC: Time-Equivariant Non-Contrastive Learning for Predicting Disease Progression From Longitudinal OCTs. IEEE Trans. Medical Imaging 43(9): 3200-3210 (2024) - [c8]Arunava Chakravarty, Taha Emre, Dmitry A. Lachinov, Antoine Rivail, Hendrik P. N. Scholl, Lars Fritsche, Sobha Sivaprasad, Daniel Rueckert, Andrew J. Lotery, Ursula Schmidt-Erfurth, Hrvoje Bogunovic:
Forecasting Disease Progression with Parallel Hyperplanes in Longitudinal Retinal OCT. MICCAI (5) 2024: 273-283 - [i14]Taha Emre, Arunava Chakravarty, Dmitrii A. Lachinov, Antoine Rivail, Ursula Schmidt-Erfurth, Hrvoje Bogunovic:
Time-Equivariant Contrastive Learning for Degenerative Disease Progression in Retinal OCT. CoRR abs/2405.09404 (2024) - [i13]Arunava Chakravarty, Taha Emre, Dmitry A. Lachinov, Antoine Rivail, Hendrik P. N. Scholl, Lars Fritsche, Sobha Sivaprasad, Daniel Rueckert, Andrew J. Lotery, Ursula Schmidt-Erfurth, Hrvoje Bogunovic:
Forecasting Disease Progression with Parallel Hyperplanes in Longitudinal Retinal OCT. CoRR abs/2409.20195 (2024) - 2023
- [j3]Botond Fazekas
Segmentation of Bruch's Membrane in Retinal OCT With AMD Using Anatomical Priors and Uncertainty Quantification. IEEE J. Biomed. Health Informatics 27(1): 41-52 (2023) - [c7]Botond Fazekas, José Morano, Dmitry A. Lachinov, Guilherme Aresta, Hrvoje Bogunovic:
Adapting Segment Anything Model (SAM) for Retinal OCT. OMIA@MICCAI 2023: 92-101 - [c6]José Morano
Self-supervised Learning via Inter-modal Reconstruction and Feature Projection Networks for Label-Efficient 3D-to-2D Segmentation. MICCAI (4) 2023: 589-599 - [i12]José Morano, Guilherme Aresta, Dmitrii A. Lachinov, Julia Mai, Ursula Schmidt-Erfurth, Hrvoje Bogunovic:
Self-supervised learning via inter-modal reconstruction and feature projection networks for label-efficient 3D-to-2D segmentation. CoRR abs/2307.03008 (2023) - [i11]Botond Fazekas, José Morano, Dmitrii A. Lachinov, Guilherme Aresta, Hrvoje Bogunovic:
SAMedOCT: Adapting Segment Anything Model (SAM) for Retinal OCT. CoRR abs/2308.09331 (2023) - [i10]Taha Emre, Arunava Chakravarty, Antoine Rivail, Dmitrii A. Lachinov, Oliver Leingang, Sophie Riedl, Julia Mai, Hendrik P. N. Scholl, Sobha Sivaprasad, Daniel Rueckert, Andrew J. Lotery, Ursula Schmidt-Erfurth, Hrvoje Bogunovic:
3DTINC: Time-Equivariant Non-Contrastive Learning for Predicting Disease Progression from Longitudinal OCTs. CoRR abs/2312.16980 (2023) - 2022
- [c5]Botond Fazekas, Guilherme Aresta, Dmitry A. Lachinov, Sophie Riedl, Julia Mai
SD-LayerNet: Semi-supervised Retinal Layer Segmentation in OCT Using Disentangled Representation with Anatomical Priors. MICCAI (8) 2022: 320-329 - [i9]Botond Fazekas, Guilherme Aresta, Dmitrii A. Lachinov, Sophie Riedl, Julia Mai, Ursula Schmidt-Erfurth, Hrvoje Bogunovic:
SD-LayerNet: Semi-supervised retinal layer segmentation in OCT using disentangled representation with anatomical priors. CoRR abs/2207.00458 (2022) - [i8]Botond Fazekas, Dmitrii A. Lachinov, Guilherme Aresta, Julia Mai, Ursula Schmidt-Erfurth, Hrvoje Bogunovic:
Segmentation of Bruch's Membrane in retinal OCT with AMD using anatomical priors and uncertainty quantification. CoRR abs/2210.14799 (2022) - [i7]Dmitrii A. Lachinov, Arunava Chakravarty, Christoph Grechenig, Ursula Schmidt-Erfurth, Hrvoje Bogunovic:
Learning Spatio-Temporal Model of Disease Progression with NeuralODEs from Longitudinal Volumetric Data. CoRR abs/2211.04234 (2022) - 2021
- [j2]A. Emre Kavur, Naciye Sinem Gezer, Mustafa Baris
CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation. Medical Image Anal. 69: 101950 (2021) - [c4]Dmitrii A. Lachinov
Projective Skip-Connections for Segmentation Along a Subset of Dimensions in Retinal OCT. MICCAI (1) 2021: 431-441 - [i6]Dmitrii A. Lachinov, Philipp Seeböck, Julia Mai, Ursula Schmidt-Erfurth, Hrvoje Bogunovic:
Projective Skip-Connections for Segmentation Along a Subset of Dimensions in Retinal OCT. CoRR abs/2108.00831 (2021) - 2020
- [i5]A. Emre Kavur, Naciye Sinem Gezer, Mustafa Baris, Pierre-Henri Conze, Vladimir Groza, Duc Duy Pham, Soumick Chatterjee
CHAOS Challenge - Combined (CT-MR) Healthy Abdominal Organ Segmentation. CoRR abs/2001.06535 (2020) - [i4]Dmitry A. Lachinov, Elena Shipunova, Vadim Turlapov:
Knowledge Distillation for Brain Tumor Segmentation. CoRR abs/2002.03688 (2020) - [i3]Dmitry A. Lachinov, Alexandra Getmanskaya, Vadim Turlapov:
Cephalometric Landmark Regression with Convolutional Neural Networks on 3D Computed Tomography Data. CoRR abs/2007.10052 (2020)
2010 – 2019
- 2019
- [c3]Dmitry A. Lachinov
Knowledge Distillation for Brain Tumor Segmentation. BrainLes@MICCAI (2) 2019: 324-332 - [c2]Dmitry A. Lachinov:
Segmentation of Thoracic Organs Using Pixel Shuffle. SegTHOR@ISBI 2019 - 2018
- [j1]Dmitry A. Lachinov, A. A. Getmanskaya
Refinement of the Coherent Point Drift Registration Results by the Example of Cephalometry Problems. Program. Comput. Softw. 44(4): 248-257 (2018) - [c1]Dmitry A. Lachinov
Glioma Segmentation with Cascaded UNet. BrainLes@MICCAI (2) 2018: 189-198 - [i2]Dmitry A. Lachinov, Evgeny Vasiliev, Vadim Turlapov:
Glioma Segmentation with Cascaded Unet. CoRR abs/1810.04008 (2018) - [i1]Dmitry A. Lachinov, Vadim Turlapov:
The Coherent Point Drift for Clustered Point Sets. CoRR abs/1812.05869 (2018)
Coauthor Index
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