Glioma Segmentation with Cascaded UNet. - Dmitry A. Lachinov; Evgeny Vasiliev; Vadim Turlapov (BrainLes@MICCAI (2), 2018)

The Coherent Point Drift for Clustered Point Sets. - Dmitry A. Lachinov; Vadim Turlapov (CoRR, 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)

Knowledge Distillation for Brain Tumor Segmentation. - Dmitry A. Lachinov; Elena Shipunova; Vadim Turlapov (BrainLes@MICCAI (2), 2019)

Segmentation of Thoracic Organs Using Pixel Shuffle. - Dmitry A. Lachinov (SegTHOR@ISBI, 2019)

Cephalometric Landmark Regression with Convolutional Neural Networks on 3D Computed Tomography Data. - Dmitry A. Lachinov; Alexandra Getmanskaya; Vadim Turlapov (CoRR, 2020)

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 (MICCAI (1), 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)

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; et al. (Medical Image Anal., 2021)

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 (MICCAI (8), 2022)

Adapting Segment Anything Model (SAM) for Retinal OCT. - Botond Fazekas; José Morano; Dmitry A. Lachinov; Guilherme Aresta; Hrvoje Bogunovic (OMIA@MICCAI, 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 (MICCAI (4), 2023)

SAMedOCT: Adapting Segment Anything Model (SAM) for Retinal OCT. - Botond Fazekas; José Morano; Dmitrii A. Lachinov; Guilherme Aresta; Hrvoje Bogunovic (CoRR, 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)

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 (MICCAI (5), 2024)

Automatic Detection and Prediction of nAMD Activity Change in Retinal OCT Using Siamese Networks and Wasserstein Distance for Ordinality. - Taha Emre; Teresa Araújo; Marzieh Oghbaie; Dmitrii A. Lachinov; Guilherme Aresta; Hrvoje Bogunovic (DIAMOND/MARIO@MICCAI, 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 (MICCAI (12), 2024)

Predicting Age-related Macular Degeneration Progression from Retinal Optical Coherence Tomography with Intra-Subject Temporal Consistency. - Arunava Chakravarty; Taha Emre; Dmitrii A. Lachinov; Antoine Rivail; Ursula Schmidt-Erfurth; Hrvoje Bogunovic (MIDL, 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 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, 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; et al. (IEEE Trans. Medical Imaging, 2024)

SD-LayerNet: Robust and label-efficient retinal layer segmentation via anatomical priors. - Botond Fazekas; Guilherme Aresta; Dmitry A. Lachinov; Sophie Riedl; Julia Mai; Ursula Schmidt-Erfurth; Hrvoje Bogunovic (Comput. Methods Programs Biomed., 2025)