mlsanityData to 14 Oct 2026

SAME: Deformable Image Registration based on Self-supervised Anatomical Embeddings

arXiv 2109.11572 ↗First posted 23 Sep 2021eess.IV cs.CVcited by 21

Not on the map. Why?

Abstract (arXiv)

In this work, we introduce a fast and accurate method for unsupervised 3D medical image registration. This work is built on top of a recent algorithm SAM, which is capable of computing dense anatomical/semantic correspondences between two images at the pixel level. Our method is named SAME, which breaks down image registration into three steps: affine transformation, coarse deformation, and deep deformable registration. Using SAM embeddings, we enhance these steps by finding more coherent correspondences, and providing features and a loss function with better semantic guidance. We collect a multi-phase chest computed tomography dataset with 35 annotated organs for each patient and conduct inter-subject registration for quantitative evaluation. Results show that SAME outperforms widely-used traditional registration techniques (Elastix FFD, ANTs SyN) and learning based VoxelMorph method by at least 4.7% and 2.7% in Dice scores for two separate tasks of within-contrast-phase and across-contrast-phase registration, respectively. SAME achieves the comparable performance to the best traditional registration method, DEEDS (from our evaluation), while being orders of magnitude faster (from 45 seconds to 1.2 seconds).

Key facts. Cited by 21 papers in the map (data through 14 Oct 2026). Builds on 9 of its 20 references that are in the map. First posted on arXiv 23 Sep 2021.

Builds on

9 of 20 references.

References · 9

  1. 20163D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotationcited by 1,476
  2. 2015FlowNet: Learning Optical Flow with Convolutional Networkscited by 1,059
  3. 2018VoxelMorph: A Learning Framework for Deformable Medical Image Registrationcited by 662
  4. 2019Recursive Cascaded Networks for Unsupervised Medical Image Registrationcited by 105
  5. 2020SAM: Self-supervised Learning of Pixel-wise Anatomical Embeddings in Radiological Imagescited by 67
  6. 2019Dual-Stream Pyramid Registration Networkcited by 52
  7. 2017Progressive and Multi-Path Holistically Nested Neural Networks for Pathological Lung Segmentation from CT Imagescited by 11
  8. 2021DeepStationing: Thoracic Lymph Node Station Parsing in CT Scans using Anatomical Context Encoding and Key Organ Auto-Searchcited by 9
  9. 2020JSSR: A Joint Synthesis, Segmentation, and Registration System for 3D Multi-Modal Image Alignment of Large-scale Pathological CT Scanscited by 3

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 1; 2023: 8; 2024: 6; 2025: 3; 2026: 3.

21 papers.

Sort:

By area:

  1. 2023A survey on deep learning in medical image registration: new technologies, uncertainty, evaluation metrics, and beyondcited by 55
  2. 2023PCRLv2: A Unified Visual Information Preservation Framework for Self-supervised Pre-training in Medical Image Analysiscited by 40
  3. 2023A Robust and Interpretable Deep Learning Framework for Multi-modal Registration via Keypointscited by 25
  4. 2024Deep Learning in Medical Image Registration: Magic or Mirage?cited by 21
  5. 2023Spatially Covariant Image Registration with Text Promptscited by 18
  6. 2023SAMConvex: Fast Discrete Optimization for CT Registration using Self-supervised Anatomical Embedding and Correlation Pyramidcited by 14
  7. 2024MambaMorph: a Mamba-based Framework for Medical MR-CT Deformable Registrationcited by 10
  8. 2023SAME++: A Self-supervised Anatomical eMbeddings Enhanced medical image registration framework using stable sampling and regularized transformationcited by 9
  9. 2024RayEmb: Arbitrary Landmark Detection in X-Ray Images Using Ray Embedding Subspacecited by 6
  10. 2025IMPACT: A Generic Semantic Loss for Multimodal Medical Image Registrationcited by 5
  11. 2023A Hierarchical Descriptor Framework for On-the-Fly Anatomical Location Matching between Longitudinal Studiescited by 4
  12. 2024EfficientMorph: Parameter-Efficient Transformer-Based Architecture for 3D Image Registrationcited by 3
9 more
  1. 2023Matching in the Wild: Learning Anatomical Embeddings for Multi-Modality Imagescited by 2
  2. 2024Tumor aware recurrent inter-patient deformable image registration of computed tomography scans with lung cancercited by 2
  3. 2025UniReg: Conditional Unified Model for Medical Image Registrationcited by 2
  4. 2022Collaborative Quantization Embeddings for Intra-Subject Prostate MR Image Registrationcited by 1
  5. 2024Bayesian Unsupervised Disentanglement of Anatomy and Geometry for Deep Groupwise Image Registrationcited by 1
  6. 2025RealKeyMorph: Keypoints in Real-world Coordinates for Resolution-agnostic Image Registrationcited by 0
  7. 2026A Cautionary Tale of Self-Supervised Learning for Imaging Biomarkers: Alzheimer's Disease Case Studycited by 0
  8. 2026CoRe: Joint Optimization with Contrastive Learning for Medical Image Registrationcited by 0
  9. 2026Benchmarking Intra-Patient 3D Deformable Multimodal Image Registrationcited by 0