mlsanityData to 14 Oct 2026

Semantic Image Synthesis for Abdominal CT

arXiv 2312.06453 ↗First posted 11 Dec 2023cs.CV eess.IVcited by 10

On the map: Diffusion models → Medical imaging and segmentation

Abstract (arXiv)

As a new emerging and promising type of generative models, diffusion models have proven to outperform Generative Adversarial Networks (GANs) in multiple tasks, including image synthesis. In this work, we explore semantic image synthesis for abdominal CT using conditional diffusion models, which can be used for downstream applications such as data augmentation. We systematically evaluated the performance of three diffusion models, as well as to other state-of-the-art GAN-based approaches, and studied the different conditioning scenarios for the semantic mask. Experimental results demonstrated that diffusion models were able to synthesize abdominal CT images with better quality. Additionally, encoding the mask and the input separately is more effective than na"ive concatenating.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models. Builds on 23 of its 27 references that are in the map. First posted on arXiv 11 Dec 2023.

Builds on

23 of 27 references.

Closest ancestors · 7

Same direction, newest first

  1. 2023High-Fidelity Image Synthesis from Pulmonary Nodule Lesion Maps using Semantic Diffusion Model2 May
  2. 2022Diffusion Models for Medical Image Analysis: A Comprehensive Survey14 Nov
  3. 2022Unsupervised Medical Image Translation with Adversarial Diffusion Models17 Jul
  4. 2022Diffusion Models for Medical Anomaly Detection8 Mar
  5. 2021DiffuseMorph: Unsupervised Deformable Image Registration Using Diffusion Model9 Dec
  6. 2021Diffusion Models for Implicit Image Segmentation Ensembles6 Dec
  7. 2021Score-based diffusion models for accelerated MRI8 Oct

Other references · 16

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2020Denoising Diffusion Implicit Modelscited by 9,781
  3. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,255
  4. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,527
  5. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,761
  6. 2021Image Super-Resolution via Iterative Refinementcited by 1,511
  7. 2019Semantic Image Synthesis with Spatially-Adaptive Normalizationcited by 1,299
  8. 2022TotalSegmentator: robust segmentation of 104 anatomical structures in CT imagescited by 613
  9. 2021Tackling the Generative Learning Trilemma with Denoising Diffusion GANscited by 516
  10. 2022AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentationcited by 351
  11. 2018Medical Image Synthesis for Data Augmentation and Anonymization using Generative Adversarial Networkscited by 147
  12. 2022Semantic Image Synthesis via Diffusion Modelscited by 132
4 more
  1. 2020You Only Need Adversarial Supervision for Semantic Image Synthesiscited by 129
  2. 2018Efficient Active Learning for Image Classification and Segmentation using a Sample Selection and Conditional Generative Adversarial Networkcited by 74
  3. 2018Learning Data Augmentation for Brain Tumor Segmentation with Coarse-to-Fine Generative Adversarial Networkscited by 15
  4. 2018ScarGAN: Chained Generative Adversarial Networks to Simulate Pathological Tissue on Cardiovascular MR Scanscited by 5

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 7; 2025: 2; 2026: 1.

10 papers.

  1. 2024A Comprehensive Survey of Foundation Models in Medicinecited by 56
  2. 2024MedDiff-FM: A Diffusion-based Foundation Model for Versatile Medical Image Applicationscited by 7
  3. 2024CT Synthesis with Conditional Diffusion Models for Abdominal Lymph Node Segmentationcited by 5
  4. 2024A Comprehensive Survey on Diffusion Models and Their Applicationscited by 4
  5. 2024Image Synthesis with Class-Aware Semantic Diffusion Models for Surgical Scene Segmentationcited by 1
  6. 2024GuideGen: A Text-Guided Framework for Paired Full-torso Anatomy and CT Volume Generationcited by 0
  7. 2024Appearance Matching Adapter for Exemplar-based Semantic Image Synthesis in-the-Wildcited by 0
  8. 2025ZECO: ZeroFusion Guided 3D MRI Conditional Generationcited by 0
  9. 2025AnatoMaskGAN: GNN-Driven Slice Feature Fusion and Noise Augmentation for Medical Semantic Image Synthesiscited by 0
  10. 2026MedSyn2: Flexible Control of 3D CT Generation via Text and Semantically-Defined Segmentation Promptscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Comparative Analysis of GAN and Diffusion for MRI-to-CT translation
  2. 2023MedSyn: Text-guided Anatomy-aware Synthesis of High-Fidelity 3D CT Images
  3. 2023Conditional Image Generation with Pretrained Generative Model
  4. 2024Deep Generative Models for 3D Medical Image Synthesis
  5. 2024Multi-Conditioned Denoising Diffusion Probabilistic Model (mDDPM) for Medical Image Synthesis
  6. 2024Cross-conditioned Diffusion Model for Medical Image to Image Translation
  7. 2024Controllable Face Synthesis with Semantic Latent Diffusion Models
  8. 2026PIVM: Diffusion-Based Prior-Integrated Variation Modeling for Anatomically Precise Abdominal CT Synthesis