mlsanityData to 14 Oct 2026

Kidney Cancer Detection Using 3D-Based Latent Diffusion Models

arXiv 2601.05852 ↗First posted 9 Jan 2026cs.CVcited by 0

On the map: Diffusion models → Medical imaging and segmentation

Abstract (arXiv)

In this work, we present a novel latent diffusion-based pipeline for 3D kidney anomaly detection on contrast-enhanced abdominal CT. The method combines Denoising Diffusion Probabilistic Models (DDPMs), Denoising Diffusion Implicit Models (DDIMs), and Vector-Quantized Generative Adversarial Networks (VQ-GANs). Unlike prior slice-wise approaches, our method operates directly on an image volume and leverages weak supervision with only case-level pseudo-labels. We benchmark our approach against state-of-the-art supervised segmentation and detection models. This study demonstrates the feasibility and promise of 3D latent diffusion for weakly supervised anomaly detection. While the current results do not yet match supervised baselines, they reveal key directions for improving reconstruction fidelity and lesion localization. Our findings provide an important step toward annotation-efficient, generative modeling of complex abdominal anatomy.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models. Builds on 14 of its 20 references that are in the map. First posted on arXiv 9 Jan 2026.

Builds on

14 of 20 references.

Closest ancestors · 4

Same direction, newest first

  1. 2024Denoising Diffusion Models for 3D Healthy Brain Tissue Inpainting21 Mar
  2. 2023Unsupervised 3D out-of-distribution detection with latent diffusion models7 Jul
  3. 2023Memory-Efficient 3D Denoising Diffusion Models for Medical Image Processing27 Mar
  4. 2022Diffusion Models for Medical Anomaly Detection8 Mar

Other references · 10

  1. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  3. 2020Denoising Diffusion Implicit Modelscited by 9,781
  4. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,255
  5. 2022TotalSegmentator: robust segmentation of 104 anatomical structures in CT imagescited by 613
  6. 2022Wavelet Diffusion Models are fast and scalable Image Generatorscited by 117
  7. 2023The KiTS21 Challenge: Automatic segmentation of kidneys, renal tumors, and renal cysts in corticomedullary-phase CTcited by 103
  8. 2021nnDetection: A Self-configuring Method for Medical Object Detectioncited by 60
  9. 2025Robust Renal Mass Segmentation on CT: A Validation Study of an AI-Based Frameworkcited by 3
  10. 2023Kidney abnormality segmentation in thorax-abdomen CT scanscited by 2

Built on by

Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2026Diffusion-Based Tumor Inpainting for Renal Segmentation under Clinical Data Scarcity
  2. 2024Pancreatic Tumor Segmentation as Anomaly Detection in CT Images Using Denoising Diffusion Models
  3. 2024Multiscale Latent Diffusion Model for Enhanced Feature Extraction from Medical Images
  4. 2026Unsupervised Anatomical Feature Learning via Diffusion Models: Enhanced Medical Image Segmentation with Denoising Diffusion Probabilistic Models
  5. 2022Diffusion Models for Medical Image Analysis: A Comprehensive Survey
  6. 2023Semantic Image Synthesis for Abdominal CT
  7. 2022Fast Unsupervised Brain Anomaly Detection and Segmentation with Diffusion Models
  8. 2022Diffusion Probabilistic Models beat GANs on Medical Images