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ORCIDDmitry A. Lachinov
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2020 – today
- 2024
[j5]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. IEEE Trans. Medical Imaging 43(3): 1165-1179 (2024)- [j4]Taha Emre, Arunava Chakravarty, Antoine Rivail, Dmitry 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. IEEE Trans. Medical Imaging 43(9): 3200-3210 (2024) - [c9]Taha Emre, Arunava Chakravarty, Dmitry A. Lachinov, Antoine Rivail, Ursula Schmidt-Erfurth, Hrvoje Bogunovic:
Learning Temporally Equivariance for Degenerative Disease Progression in OCT by Predicting Future Representations. MICCAI (12) 2024: 196-206 - [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, Dmitry 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. 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, Guilherme Aresta, Dmitry 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. 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, Ursula Schmidt-Erfurth, Hrvoje Bogunovic:
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, Sinem Aslan, Pierre-Henri Conze, Vladimir Groza, Duc Duy Pham, Soumick Chatterjee, Philipp Ernst, Savas Özkan, Bora Baydar, Dmitry A. Lachinov, Shuo Han, Josef Pauli, Fabian Isensee, Matthias Perkonigg, Rachana Sathish, Ronnie Rajan, Debdoot Sheet, Gurbandurdy Dovletov, Oliver Speck, Andreas Nürnberger, Klaus H. Maier-Hein, Gözde B. Akar, Gözde B. Ünal, Oguz Dicle, M. Alper Selver:
CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation. Medical Image Anal. 69: 101950 (2021) - [c4]Dmitrii A. Lachinov, Philipp Seeböck, Julia Mai, Felix Goldbach, Ursula Schmidt-Erfurth, Hrvoje Bogunovic:
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, Philipp Ernst, Savas Özkan, Bora Baydar, Dmitry A. Lachinov, Shuo Han, Josef Pauli, Fabian Isensee, Matthias Perkonigg, Rachana Sathish, Ronnie Rajan, Sinem Aslan, Debdoot Sheet, Gurbandurdy Dovletov, Oliver Speck, Andreas Nürnberger, Klaus H. Maier-Hein, Gözde B. Akar, Gözde B. Ünal, Oguz Dicle, M. Alper Selver:
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, Elena Shipunova, Vadim Turlapov:
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, V. E. Turlapov:
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, Evgeny Vasiliev, Vadim Turlapov:
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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