mlsanityData to 7 Oct 2026

Implicit Neural Representation in Medical Imaging: A Comparative Survey

arXiv 2307.16142 ↗First posted 30 Jul 2023eess.IV cs.CVcited by 88

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Abstract (arXiv)

Implicit neural representations (INRs) have gained prominence as a powerful paradigm in scene reconstruction and computer graphics, demonstrating remarkable results. By utilizing neural networks to parameterize data through implicit continuous functions, INRs offer several benefits. Recognizing the potential of INRs beyond these domains, this survey aims to provide a comprehensive overview of INR models in the field of medical imaging. In medical settings, numerous challenging and ill-posed problems exist, making INRs an attractive solution. The survey explores the application of INRs in various medical imaging tasks, such as image reconstruction, segmentation, registration, novel view synthesis, and compression. It discusses the advantages and limitations of INRs, highlighting their resolution-agnostic nature, memory efficiency, ability to avoid locality biases, and differentiability, enabling adaptation to different tasks. Furthermore, the survey addresses the challenges and considerations specific to medical imaging data, such as data availability, computational complexity, and dynamic clinical scene analysis. It also identifies future research directions and opportunities, including integration with multi-modal imaging, real-time and interactive systems, and domain adaptation for clinical decision support. To facilitate further exploration and implementation of INRs in medical image analysis, we have provided a compilation of cited studies along with their available open-source implementations on hrefhttps://github.com/mindflow-institue/Awesome-Implicit-Neural-Representations-in-Medical-imaging. Finally, we aim to consistently incorporate the most recent and relevant papers regularly.

Key facts. Cited by 88 papers in the map (data through 7 Oct 2026). Builds on 43 of its 73 references that are in the map. First posted on arXiv 30 Jul 2023.

Builds on

43 of 73 references.

References · 43

  1. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  2. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,698
  3. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,682
  4. 2020Implicit Neural Representations with Periodic Activation Functionscited by 2,214
  5. 2020Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domainscited by 2,170
  6. 2018Occupancy Networks: Learning 3D Reconstruction in Function Spacecited by 2,037
  7. 2018On the Spectral Bias of Neural Networkscited by 1,321
  8. 2018Learning Implicit Fields for Generative Shape Modelingcited by 1,060
  9. 2020GRAF: Generative Radiance Fields for 3D-Aware Image Synthesiscited by 688
  10. 2021Neural Fields in Visual Computing and Beyondcited by 539
  11. 2020Deep Local Shapes: Learning Local SDF Priors for Detailed 3D Reconstructioncited by 321
  12. 2022MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile Architecturescited by 308
31 more
  1. 2022Diffusion Models for Medical Image Analysis: A Comprehensive Surveycited by 269
  2. 2021NeRV: Neural Representations for Videoscited by 255
  3. 2023WIRE: Wavelet Implicit Neural Representationscited by 220
  4. 2019On instabilities of deep learning in image reconstruction - Does AI come at a cost?cited by 211
  5. 2022Medical Image Segmentation Review: The success of U-Netcited by 190
  6. 2019DIST: Rendering Deep Implicit Signed Distance Function with Differentiable Sphere Tracingcited by 179
  7. 2021NeRP: Implicit Neural Representation Learning with Prior Embedding for Sparsely Sampled Image Reconstructioncited by 145
  8. 2022Neural Rendering for Stereo 3D Reconstruction of Deformable Tissues in Robotic Surgerycited by 122
  9. 2021Dynamic CT Reconstruction from Limited Views with Implicit Neural Representations and Parametric Motion Fieldscited by 69
  10. 2022MedNeRF: Medical Neural Radiance Fields for Reconstructing 3D-aware CT-Projections from a Single X-raycited by 66
  11. 2023Advances in Medical Image Analysis with Vision Transformers: A Comprehensive Reviewcited by 62
  12. 2021Neural Re-Rendering of Humans from a Single Imagecited by 59
  13. 2021An Arbitrary Scale Super-Resolution Approach for 3D MR Images via Implicit Neural Representationcited by 47
  14. 2021IREM: High-Resolution Magnetic Resonance (MR) Image Reconstruction via Implicit Neural Representationcited by 42
  15. 2023DNeRV: Modeling Inherent Dynamics via Difference Neural Representation for Videoscited by 42
  16. 2019A Skeleton-bridged Deep Learning Approach for Generating Meshes of Complex Topologies from Single RGB Imagescited by 37
  17. 2021CoIL: Coordinate-based Internal Learning for Imaging Inverse Problemscited by 33
  18. 2019Going Deep in Medical Image Analysis: Concepts, Methods, Challenges and Future Directionscited by 24
  19. 2022SNAF: Sparse-view CBCT Reconstruction with Neural Attenuation Fieldscited by 23
  20. 2021ImageCHD: A 3D Computed Tomography Image Dataset for Classification of Congenital Heart Diseasecited by 16
  21. 2022TINC: Tree-structured Implicit Neural Compressioncited by 14
  22. 2022SCI: A Spectrum Concentrated Implicit Neural Compression for Biomedical Datacited by 13
  23. 2022Implicit Neural Representations for Generative Modeling of Living Cell Shapescited by 12
  24. 2021Multi-Head ReLU Implicit Neural Representation Networkscited by 10
  25. 2021Binary segmentation of medical images using implicit spline representations and deep learningcited by 7
  26. 2023Implicit Neural Representations for Modeling of Abdominal Aortic Aneurysm Progressioncited by 6
  27. 2021NeRD: Neural Representation of Distribution for Medical Image Segmentationcited by 5
  28. 2021Ensemble Neural Representation Networkscited by 5
  29. 2022SINCO: A Novel structural regularizer for image compression using implicit neural representationscited by 4
  30. 2023TbExplain: A Text-based Explanation Method for Scene Classification Models with the Statistical Prediction Correctioncited by 4
  31. 2023EnTri: Ensemble Learning with Tri-level Representations for Explainable Scene Recognitioncited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 12; 2024: 29; 2025: 28; 2026: 19.

88 papers.

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  1. 2024A Survey on 3D Gaussian Splattingcited by 221
  2. 2024Where Do We Stand with Implicit Neural Representations? A Technical and Performance Surveycited by 41
  3. 2023Loss Functions in the Era of Semantic Segmentation: A Survey and Outlookcited by 33
  4. 2023INCODE: Implicit Neural Conditioning with Prior Knowledge Embeddingscited by 31
  5. 20233DGR-CT: Sparse-View CT Reconstruction with a 3D Gaussian Representationcited by 24
  6. 2023I-MedSAM: Implicit Medical Image Segmentation with Segment Anythingcited by 22
  7. 2023Continual Learning in Medical Image Analysis: A Comprehensive Review of Recent Advancements and Future Prospectscited by 22
  8. 2023Efficient Deformable Tissue Reconstruction via Orthogonal Neural Planecited by 20
  9. 2024Nonparametric Teaching of Implicit Neural Representationscited by 13
  10. 2023DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion Delineationcited by 12
  11. 2024Implicit Neural Representations for Robust Joint Sparse-View CT Reconstructioncited by 9
  12. 2024Neural Radiance Fields in Medical Imaging: A Surveycited by 7
38 more
  1. 2024TOGS: Gaussian Splatting with Temporal Opacity Offset for Real-Time 4D DSA Renderingcited by 7
  2. 2024DRACO: Differentiable Reconstruction for Arbitrary CBCT Orbitscited by 6
  3. 2025Quantum Visual Fields with Neural Amplitude Encodingcited by 6
  4. 2023Self-supervised Semantic Segmentation: Consistency over Transformationcited by 5
  5. 2024Dynamic NeRF: A Reviewcited by 5
  6. 2023Entangled View-Epipolar Information Aggregation for Generalizable Neural Radiance Fieldscited by 4
  7. 2024Understanding the dynamics of the frequency bias in neural networkscited by 4
  8. 2024Blaze3DM: Marry Triplane Representation with Diffusion for 3D Medical Inverse Problem Solvingcited by 4
  9. 2024IM-MoCo: Self-supervised MRI Motion Correction using Motion-Guided Implicit Neural Representationscited by 4
  10. 2024NeRF-CA: Dynamic Reconstruction of X-ray Coronary Angiography with Extremely Sparse-viewscited by 4
  11. 2024TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detectioncited by 4
  12. 2024Enhancing Implicit Neural Representations via Symmetric Power Transformationcited by 4
  13. 2025Continuous Representation Methods, Theories, and Applications: An Overview and Perspectivescited by 4
  14. 2023Unlocking Fine-Grained Details with Wavelet-based High-Frequency Enhancement in Transformerscited by 3
  15. 2023CoNeS: Conditional neural fields with shift modulation for multi-sequence MRI translationcited by 3
  16. 2024Ray-driven Spectral CT Reconstruction Based on Neural Base-Material Fieldscited by 3
  17. 2024NeuroGauss4D-PCI: 4D Neural Fields and Gaussian Deformation Fields for Point Cloud Interpolationcited by 3
  18. 2024CPT-Interp: Continuous sPatial and Temporal Motion Modeling for 4D Medical Image Interpolationcited by 3
  19. 2024ImplicitTerrain: a Continuous Surface Model for Terrain Data Analysiscited by 3
  20. 2024Estimating Neural Orientation Distribution Fields on High Resolution Diffusion MRI Scanscited by 3
  21. 2025ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Datacited by 3
  22. 2024Towards the Spectral bias Alleviation by Normalizations in Coordinate Networkscited by 2
  23. 2024Coordinate-based Speed of Sound Recovery for Aberration-Corrected Photoacoustic Computed Tomographycited by 2
  24. 2025Towards Understanding the Benefits of Neural Network Parameterizations in Geophysical Inversions: A Study With Neural Fieldscited by 2
  25. 2025A topology-preserving three-stage framework for fully-connected coronary artery extractioncited by 2
  26. 2025Exploring Kernel Transformations for Implicit Neural Representationscited by 2
  27. 2025Physiological neural representation for personalised tracer kinetic parameter estimation from dynamic PETcited by 2
  28. 2025ViT-NeBLa: A Hybrid Vision Transformer and Neural Beer-Lambert Framework for Single-View 3D Reconstruction of Oral Anatomy from Panoramic Radiographscited by 2
  29. 2025HNOSeg-XS: Extremely Small Hartley Neural Operator for Efficient and Resolution-Robust 3D Image Segmentationcited by 2
  30. 2025FM-SIREN & FM-FINER: Implicit Neural Representation Using Nyquist-based Orthogonalitycited by 2
  31. 2025NTK-Guided Implicit Neural Teachingcited by 2
  32. 2024ACCELERATION: Sequentially-scanning DECT Imaging Using High Temporal Resolution Image Reconstruction And Temporal Extrapolationcited by 1
  33. 2024SeCo-INR: Semantically Conditioned Implicit Neural Representations for Improved Medical Image Super-Resolutioncited by 1
  34. 2024Fast Medical Shape Reconstruction via Meta-learned Implicit Neural Representationscited by 1
  35. 2024Selective Test-Time Adaptation for Unsupervised Anomaly Detection using Neural Implicit Representationscited by 1
  36. 2025Generating visual explanations from deep networks using implicit neural representationscited by 1
  37. 2025QFGN: A Quantum Approach to High-Fidelity Implicit Neural Representationscited by 1
  38. 2025COSMO-INR: Complex Sinusoidal Modulation for Implicit Neural Representationscited by 1

50 most cited of 88 All 88 (JSON)