Dmitry A. Lachinov

According to our database, Dmitry A. Lachinov authored at least 19 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

3DTINC: Time-Equivariant Non-Contrastive Learning for Predicting Disease Progression From Longitudinal OCTs.

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

IEEE Trans. Medical Imaging, September, 2024

Learning Spatio-Temporal Model of Disease Progression With NeuralODEs From Longitudinal Volumetric Data.

Dmitrii A. Lachinov, Arunava Chakravarty, Christoph Grechenig, Ursula Schmidt-Erfurth, Hrvoje Bogunovic

IEEE Trans. Medical Imaging, March, 2024

Time-Equivariant Contrastive Learning for Degenerative Disease Progression in Retinal OCT.

Taha Emre, Arunava Chakravarty, Dmitrii A. Lachinov, Antoine Rivail, Ursula Schmidt-Erfurth, Hrvoje Bogunovic

CoRR, 2024

Learning Temporally Equivariance for Degenerative Disease Progression in OCT by Predicting Future Representations.

Taha Emre, Arunava Chakravarty, Dmitry A. Lachinov, Antoine Rivail, Ursula Schmidt-Erfurth, Hrvoje Bogunovic

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Forecasting Disease Progression with Parallel Hyperplanes in Longitudinal Retinal OCT.

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

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

2023

Segmentation of Bruch's Membrane in Retinal OCT With AMD Using Anatomical Priors and Uncertainty Quantification.

Botond Fazekas, Dmitry A. Lachinov, Guilherme Aresta, Julia Mai, Ursula Schmidt-Erfurth, Hrvoje Bogunovic

IEEE J. Biomed. Health Informatics, 2023

SAMedOCT: Adapting Segment Anything Model (SAM) for Retinal OCT.

Botond Fazekas, José Morano, Dmitrii A. Lachinov, Guilherme Aresta, Hrvoje Bogunovic

CoRR, 2023

Self-supervised Learning via Inter-modal Reconstruction and Feature Projection Networks for Label-Efficient 3D-to-2D Segmentation.

José Morano, Guilherme Aresta, Dmitry A. Lachinov, Julia Mai, Ursula Schmidt-Erfurth, Hrvoje Bogunovic

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Adapting Segment Anything Model (SAM) for Retinal OCT.

Botond Fazekas, José Morano, Dmitry A. Lachinov, Guilherme Aresta, Hrvoje Bogunovic

Proceedings of the Ophthalmic Medical Image Analysis - 10th International Workshop, 2023

2022

SD-LayerNet: Semi-supervised Retinal Layer Segmentation in OCT Using Disentangled Representation with Anatomical Priors.

Botond Fazekas, Guilherme Aresta, Dmitry A. Lachinov, Sophie Riedl, Julia Mai, Ursula Schmidt-Erfurth, Hrvoje Bogunovic

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

2021

CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation.

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

Medical Image Anal., 2021

Projective Skip-Connections for Segmentation Along a Subset of Dimensions in Retinal OCT.

Dmitrii A. Lachinov, Philipp Seeböck, Julia Mai, Ursula Schmidt-Erfurth, Hrvoje Bogunovic

CoRR, 2021

Projective Skip-Connections for Segmentation Along a Subset of Dimensions in Retinal OCT.

Dmitrii A. Lachinov, Philipp Seeböck, Julia Mai, Felix Goldbach, Ursula Schmidt-Erfurth, Hrvoje Bogunovic

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

2020

Cephalometric Landmark Regression with Convolutional Neural Networks on 3D Computed Tomography Data.

Dmitry A. Lachinov, Alexandra Getmanskaya, Vadim Turlapov

CoRR, 2020

2019

Segmentation of Thoracic Organs Using Pixel Shuffle.

Dmitry A. Lachinov

Proceedings of the 2019 Challenge on Segmentation of THoracic Organs at Risk in CT Images, 2019

Knowledge Distillation for Brain Tumor Segmentation.

Dmitry A. Lachinov, Elena Shipunova, Vadim Turlapov

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019

2018

Refinement of the Coherent Point Drift Registration Results by the Example of Cephalometry Problems.

Dmitry A. Lachinov, A. A. Getmanskaya, V. E. Turlapov

Program. Comput. Softw., 2018

The Coherent Point Drift for Clustered Point Sets.

Dmitry A. Lachinov, Vadim Turlapov

CoRR, 2018

Glioma Segmentation with Cascaded UNet.

Dmitry A. Lachinov, Evgeny Vasiliev, Vadim Turlapov

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018