3D Medical Image Segmentation

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Overview

This field develops methods that label anatomical structures and disease in 3D CT, MRI, PET, and other scans, supporting diagnosis, treatment planning, and quantitative analysis. U-Net and nnU-Net remain common baselines, alongside Transformer and state-space models; newer work also uses anatomical and topological constraints, foundation models with prompts, and efficient ways to process volumes. To reduce dependence on costly voxel-level labels, researchers use self-supervised pretraining, synthetic data, semi-supervised learning, and interactive correction, evaluating methods on tasks such as BraTS, BTCV, and ACDC. A central challenge is that strong scores on familiar datasets may not hold across hospitals, scanners, or modalities, while thin structures, uncertain boundaries, and limited compute make reliable clinical deployment difficult.

Latest papers

CardsList

213 papers14 papers in the last four weeks, down 53% on the four weeks before. 0.1% of all new papers.

  1. Instance Awareness of Multi-class Semantic Segmentation Loss Functions

    Apr 27, 2026Soumya Snigdha Kundu, Florian Kofler, Marina Ivory +3Class-Imbalanced LearningImage Segmentation

    1King’s College London · University of Tübingen · 3Technical University of Munich +1

  2. Learning from Noisy Prompts: Saliency-Guided Prompt Distillation for Robust Segmentation with SAM

    Apr 25, 2026Jingxuan Kang, Ziqi Zhang, Shaoming Zheng +9Medical Imaging Foundation ModelsPromptable Image Segmentation

    Imperial College London · Beihang University · National Health Service +1

  3. MAE-Based Self-Supervised Pretraining for Data-Efficient Medical Image Segmentation Using nnFormer

    Apr 22, 2026R. M. Krishna Sureddi, T. Satyanarayana Murthy, Nomula Varsha Reddy +2Self-Supervised Pre-TrainingMedical Image Segmentation

    Information Technology, Chaitanya Bharathi Institute of Technology, Hyderabad, India

  4. CrossPan: A Comprehensive Benchmark for Cross-Sequence Pancreas MRI Segmentation and Generalization

    Apr 20, 2026Linkai Peng, Cuiling Sun, Zheyuan Zhang +10Image SegmentationMagnetic Resonance Imaging

    Department of Radiology, Northwestern University, Chicago, USA. · Department of Electrical and Computer Engineering, Northwestern University, Evanston, USA. · Department of Computer Science, Northwestern University, Evanston, USA. +4

  5. Align then Refine: Text-Guided 3D Prostate Lesion Segmentation

    Apr 20, 2026Cuiling Sun, Linkai Peng, Adam Murphy +9Cross-Modality Medical Image SegmentationText-Guided Image Segmentation

    Department of Radiology, Northwestern University, Chicago, USA · Department of Urology, Northwestern University, Chicago, USA · Center for Cancer Research, National Cancer Institute, Bethesda, USA

  6. AI Approach for MRI-only Full-Spine Vertebral Segmentation and 3D Reconstruction in Paediatric Scoliosis

    Apr 20, 2026Nathasha Naranpanawa, Maree T. Izatt, Robert D. Labrom +23D ReconstructionMagnetic Resonance Imaging

    1Biomechanics and Spine Research Group, School of Mechanical, Medical, and Process Engineering, Faculty of Engineering, Queensland University of Technology, Brisbane · Centre for Biomedical Technologies, School of Mechanical, Medical and Process Engineering, Faculty of Engineering, Queensland University of Technology, Brisbane · 3Orthopaedics Department, Queensland Children’s Hospital, Brisbane, Australia

  7. SGP-SAM: Self-Gated Prompting for Transferring 3D Segment Anything Models to Lesion Segmentation

    Apr 19, 2026Zequan Yao, Zixuan Tang, Jielin Ma +1Image SegmentationMedical Imaging Foundation Models

    School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen China.

  8. A 3D SAM-Based Progressive Prompting Framework for Multi-Task Segmentation of Radiotherapy-induced Normal Tissue Injuries in Limited-Data Settings

    Apr 15, 2026Caiwen Jiang, Lei Zeng, Wei LiuMedical Image Segmentation3D Medical Image Segmentation

    Department of Radiation Oncology, Mayo Clinic, Phoenix, Arizona, USA

  9. A Workflow to Efficiently Generate Dense Tissue Ground Truth Masks for Digital Breast Tomosynthesis

    Apr 13, 2026Tamerlan Mustafaev, Oleg Kruglov, Margarita Zuley +6Medical Image Segmentation3D Medical Image Segmentation

    Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA · Center of Informatics, Federal University of Paraíba, Paraiba, BRA · Department of Radiology, University of Pennsylvania, Pennsylvania, USA +1

  10. Efficient KernelSHAP Explanations for Patch-based 3D Medical Image Segmentation

    Apr 13, 2026Ricardo Coimbra Brioso, Giulio Sichili, Damiano Dei +4Explainable Medical Image AnalysisSHAP Feature Attribution

    Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy · Radiotherapy and Radiosurgery Department, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy · Scuola di Specializzazione di Fisica Medica, Università Degli Studi di Milano, Milan, Italy +1

  11. RADA: Region-Aware Dual-encoder Auxiliary learning for Barely-supervised Medical Image Segmentation

    Apr 13, 2026Shuang Zeng, Boxu Xie, Lei Zhu +6Medical Image Segmentation3D Medical Image Segmentation

  12. Weakly-Supervised Lung Nodule Segmentation via Training-Free Guidance of 3D Rectified Flow

    Apr 9, 2026Richard Petersen, Fredrik Kahl, Jennifer AlvénWeakly Supervised Image Segmentation3D Medical Image Segmentation

    Chalmers University of Technology, Gothenburg, Sweden

  13. T-Gated Adapter: A Lightweight Temporal Adapter for Vision-Language Medical Segmentation

    Apr 9, 2026Pranjal KhadkaMedical Image Segmentation3D Medical Image Segmentation

    Independent Researcher

  14. Benchmarking Deep Learning for Future Liver Remnant Segmentation in Colorectal Liver Metastasis

    Apr 9, 2026Anthony T. Wu, Arghavan Rezvani, Kela Liu +4Medical Image Segmentation3D Medical Image Segmentation

    University of California, Irvine Donald Bren School of Information and Computer Science · University of California, Irvine School of Medicine

  15. GPAFormer: Graph-guided Patch Aggregation Transformer for Efficient 3D Medical Image Segmentation

    Apr 8, 2026Chung-Ming Lo, I-Yun Liu, Wei-Yang LinMulti-Organ SegmentationMedical Image Segmentation

    Institute of Artificial Intelligence Innovation, Industry Academia Innovation School, National Yang Ming Chiao Tung University · Department of Computer Science and Information Engineering, National Chung Cheng University

  16. Geometrical Cross-Attention and Nonvoid Voxelization for Efficient 3D Medical Image Segmentation

    Apr 7, 2026Chenxin Yuan, Shoupeng Chen, Haojiang Ye +33D Medical Image Segmentation3D ViTs

    Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen, 518100, Guangdong, China · School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, 639798, Singapore · School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, Shenzhen, 518172, Guangdong, China +2

  17. Why Invariance is Not Enough for Biomedical Domain Generalization and How to Fix It

    Apr 2, 2026Sebo Diaz, Polina Golland, Elfar Adalsteinsson +1Domain Generalization for Semantic SegmentationMedical Image Segmentation

    MIT · MIT, MGH, HMS

  18. Multicentric thrombus segmentation using an attention-based recurrent network with gradual modality dropout

    Apr 1, 2026Sofia Vargas-Ibarra, Vincent Vigneron, Hichem Maaref +1Medical Image Segmentation3D Medical Image Segmentation

    Universite Evry Paris-Saclay, IBISC, 34 Rue du Pelvoux, Evry-Courcouronnes, France · SAMOVAR, Télécom SudParis, Institut Polytechnique de Paris, 34 Rue du Pelvoux, Palaiseau, France

  19. Automated Detection of Multiple Sclerosis Lesions on 7-tesla MRI Using U-net and Transformer-based Segmentation

    Apr 1, 2026Michael Maynord, Minghui Liu, Cornelia Fermüller +4Medical Image Segmentation3D Medical Image Segmentation

    Department of Computer, Science University of Maryland College Park, College Park, 20742, MD, USA · Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA · Baltimore VA Medical Center, VA Maryland Healthcare System, Baltimore, MD, 21201, USA

  20. FOSCU: Feasibility of Synthetic MRI Generation via Duo-Diffusion Models for Enhancement of 3D U-Nets in Hepatic Segmentation

    Mar 31, 2026Youngung Han, Kyeonghun Kim, Seoyoung Ju +8Medical Image SegmentationSynthetic Data Augmentation

    Seoul National University · OUTTA · Sangmyung University +4

  21. C2W-Tune: Cavity-to -Wall Transfer Learning for Thin Atrial Wall Segmentation in 3D LGE-MRI

    Mar 26, 2026Yusri Al-Sanaani, Rebecca Thornhill, Sreeraman RajanMedical Image Segmentation3D Medical Image Segmentation

    Systems and Computer Engineering, Carleton University, Ottawa, Canada · Department of Radiology, University of Ottawa, Ottawa, Canada

  22. Few-Shot Left Atrial Wall Segmentation in 3D LGE MRI via Meta-Learning

    Mar 26, 2026Yusri Al-Sanaani, Rebecca Thornhill, Pablo Nery +5Medical Image Segmentation3D Medical Image Segmentation

    Department of Systems and Computer Engineering, Carleton University, Ottawa, Canada · Department of Radiology, Radiation Oncology, and Medical Physics, University of Ottawa, Ottawa, Canada · Division of Cardiology, Department of Medicine, University of Ottawa Heart Institute, Ottawa, Canada

  23. Harnessing Lightweight Transformer with Contextual Synergic Enhancement for Efficient 3D Medical Image Segmentation

    Mar 24, 2026Xinyu Liu, Zhen Chen, Wuyang Li +23D Medical Image Segmentation3D ViTs

    Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR · Centre for Artificial Intelligence and Robotics (CAIR), Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences, Hong Kong SAR

  24. FDIF: Formula-Driven supervised Learning with Implicit Functions for 3D Medical Image Segmentation

    Mar 24, 2026Yukinori Yamamoto, Kazuya Nishimura, Tsukasa Fukusato +33D Medical Image SegmentationMedical Image Representation Learning

    Waseda University · National Institute of Advanced Industrial Science and Technology · The University of Osaka +1

  25. Automatic Segmentation of 3D CT scans with SAM2 using a zero-shot approach

    Mar 24, 2026Miquel Lopez Escoriza, Pau Amargant Alvarez3D Medical Image SegmentationZero-Shot Medical Image Segmentation

    Department of Computer Science, EPFL, Switzerland

  26. NeuroSeg Meets DINOv3: Transferring 2D Self-Supervised Visual Priors to 3D Neuron Segmentation via DINOv3 Initialization

    Mar 24, 2026Yik San Cheng, Runkai Zhao, Weidong Cai3D Medical Image SegmentationNeuroimaging

    The University of Sydney

  27. SegMaFormer: A Hybrid State-Space and Transformer Model for Efficient Segmentation

    Mar 23, 2026Duy D. Nguyen, Phat T. Tran-TruongHybrid Transformer-State Space Model Architectures3D Medical Image Segmentation

    Department of Software Engineering, Faculty of Computer Science and Engineering, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, Dien Hong Ward, Ho Chi Minh City, Vietnam · Vietnam National University Ho Chi Minh City, Linh Trung Ward, Ho Chi Minh City, Vietnam

  28. Multi-View Deformable Convolution Meets Visual Mamba for Coronary Artery Segmentation

    Mar 23, 2026Xiaochan Yuan, Pai ZengCoronary Artery Segmentation3D Medical Image Segmentation

    Sichuan Agricultural University

  29. PGR-Net: Prior-Guided ROI Reasoning Network for Brain Tumor MRI Segmentation

    Mar 23, 2026Jiacheng Lu, Hui Ding, Shiyu Zhang +1Image SegmentationBrain Tumor Segmentation

    College of Information Engineering, Capital Normal University, Beijing, China · School of Artificial Intelligence, China University of Mining and Technology-Beijing, Beijing, China

  30. Probing and Inducing Clinical Modality Grounding in Brain Tumor Segmentation

    Mar 20, 2026Lokendra Kumar, Shubham Aggarwal3D Medical Image SegmentationHyper-Connections