Awesome-3D-Controllable-Models-in-Medical-Shapes

Contents

• 1️⃣. General 3D shape generation/reconstruction (NeRF/SDF/Diffusion/implicit representation, etc.)
• 2️⃣. Medical anatomical shape modeling and geometric mesh reconstruction (heart/blood vessels/bones/organs, etc.)
• 3️⃣. 3D/4D temporal medical image generation and diffusion model (including controllable generation)
• 4️⃣. Medical image segmentation/classification with Transformer/Mamba/CNN
• 5️⃣. Applications and Overview of Transformer/ViT in Medical Imaging
• 6️⃣. 3D Shape Generation, Datasets, and Reviews (General + Medical)
• 7️⃣. Medical basic network/model training techniques (ViT general pre-training, etc.)
• 8️⃣. 3D Reconstruction of Natural Scenes / 3D Printing and Clinical Applications
• 9️⃣. Point cloud / Statistical shape / Point cloud diffusion and completion
• 🔟. Skeleton, vascular tree, and topology (reconstruction/segmentation/generation)

Paper List

1.General 3D shape generation/reconstruction (NeRF/SDF/Diffusion/implicit representation, etc.)

Latent-NeRF for Shape-Guided Generation of 3D Shapes and Textures

Gal Metzer, Elad Richardson, Or Patashnik, Raja Giryes, Daniel Cohen-Or

[14th Nov., 2022] [CVPR 2023]

[Paper]

Gradient-SDF: A Semi-Implicit Surface Representation for 3D Reconstruction

Christiane Sommer, Lu Sang, David Schubert, Daniel Cremers

[26th Nov., 2021] [CVPR 2022]

[Paper]

SDFusion: Multimodal 3D Shape Completion, Reconstruction, and Generation

Yen-Chi Cheng, Hsin-Ying Lee, Sergey Tulyakov, Alexander Schwing, Liangyan Gui

[8th Dec., 2022] [CVPR 2023]

[Paper]

LION: Latent Point Diffusion Models for 3D Shape Generation

Xiaohui Zeng, Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany, Sanja Fidler, Karsten Kreis

[12th Oct., 2022] [NeurIPS 2022]

[Paper]

AutoSDF: Shape Priors for 3D Completion, Reconstruction and Generation

Paritosh Mittal, Yen-Chi Cheng, Maneesh Singh, Shubham Tulsiani

[17th Mar., 2022] [CVPR 2022]

[Paper]

Diffusion-SDF: Text-to-Shape via Voxelized Diffusion

Muheng Li, Yueqi Duan, Jie Zhou, Jiwen Lu

[6th Dec., 2022] [CVPR 2022]

[Paper]

SDF‐StyleGAN: Implicit SDF‐Based StyleGAN for 3D Shape Generation

Xin-Yang Zheng, Yang Liu, Peng-Shuai Wang, Xin Tong

[24th Jun., 2022] [SGP 2022]

[Paper]

Towards Implicit Text-Guided 3D Shape Generation

Zhengzhe Liu, Yi Wang, Xiaojuan Qi, Chi-Wing Fu

[28th Mar., 2022] [CVPR 2022]

[Paper]

Texture synthesis for 3D shape representation

G. Gorla; V. Interrante; G. Sapiro

[Oct.–Dec., 2003] [IEEE TVCG, 2003]

[Paper]

3D Shape Generation and Completion through Point-Voxel Diffusion

Linqi Zhou, Yilun Du, Jiajun Wu

[8th Apr., 2021] [ICCV 2021]

[Paper]

Local Deep Implicit Functions for 3D Shape

Kyle Genova, Forrester Cole, Avneesh Sud, Aaron Sarna, Thomas Funkhouser

[12th Dec., 2019] [CVPR 2020]

[Paper]

Implicit Geometric Regularization for Learning Shapes

Amos Gropp, Lior Yariv, Niv Haim, Matan Atzmon, Yaron Lipman

[24th Feb., 2020] [ICML 2020]

[Paper]

Implicit Functions in Feature Space for 3D Shape Reconstruction and Completion

Julian Chibane, Thiemo Alldieck, Gerard Pons-Moll

[15th Apr., 2020] [CVPR 2020]

[Paper]

Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapes

Towaki Takikawa, Joey Litalien, Kangxue Yin, Karsten Kreis, Charles Loop, Derek Nowrouzezahrai, Alec Jacobson, Morgan McGuire, Sanja Fidler

[26th Jan., 2021] [CVPR 2021]

[Paper]

Neural Volumetric Mesh Generator

Yan Zheng, Lemeng Wu, Xingchao Liu, Zhen Chen, Qiang Liu, Qixing Huang

[6th Oct., 2022] [NeurIPS 2022]

[Paper]

Learning Scene-Level Signed Directional Distance Function with Ellipsoidal Priors and Neural Residuals

Zhirui Dai, Hojoon Shin, Yulun Tian, Ki Myung Brian Lee, Nikolay Atanasov

[25th Mar., 2025] [arXiv 2025]

[Paper]

CrossGen: Learning and Generating Cross Fields for Quad Meshing

Qiujie Dong, Jiepeng Wang, Rui Xu, Cheng Lin, Yuan Liu, Shiqing Xin, Zichun Zhong, Xin Li, Changhe Tu, Taku Komura, Leif Kobbelt, Scott Schaefer, Wenping Wang

[8th Jun., 2025] [arXiv 2025]

[Paper]

High Resolution UDF Meshing via Iterative Networks

Federico Stella, Nicolas Talabot, Hieu Le, Pascal Fua

[21th Sep., 2025] [Neurlps 2025]

[Paper]

Reach For the Spheres: Tangency-Aware Surface Reconstruction of SDFs

Silvia Sellán, Christopher Batty, Oded Stein

[18th Aug., 2023] [arXiv 2023]

[Paper]

Marching-Primitives: Shape Abstraction from Signed Distance Function

Weixiao Liu, Yuwei Wu, Sipu Ruan, Gregory S. Chirikjian

[23th Mar., 2023] [CVPR 2023]

[Paper]

Approximating Signed Distance Fields of Implicit Surfaces with Sparse Ellipsoidal Radial Basis Function Networks

Bobo Lian, Dandan Wang, Chenjian Wu, Minxin Chen

[5th May., 2025] [arXiv 2025]

[Paper]

Differentiable Rendering of Neural SDFs through Reparameterization

Sai Praveen Bangaru, Michaël Gharbi, Tzu-Mao Li, Fujun Luan, Kalyan Sunkavalli, Miloš Hašan, Sai Bi, Zexiang Xu, Gilbert Bernstein, Frédo Durand

[10th Jun., 2022] [arXiv 2022]

[Paper]

Meshless Monte Carlo Radiation Transfer Method for Curved Geometries using Signed Distance Functions

Lewis McMillan, Graham D. Bruce, Kishan Dholakia

[15th Dec., 2021] [arXiv 2021]

[Paper]

Shape-informed surrogate models based on signed distance functions

Linying Zhang, Stefano Pagani, Jun Zhang, Francesco Regazzoni

[19th Sep., 2024] [arXiv 2024]

[Paper]

DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation

Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, Steven Lovegrove

[16th Jan., 2019] [arXiv 2019]

[Paper]

Push-Forward Signed Distance Functions enable interpretable and robust shape representation

Roua Rouatbi , Juan Esteban Suarez, Ivo F. Sbalzarini

[28th Oct., 2024] [arXiv 2024]

[Paper]

GenSDF: Two-Stage Learning of Generalizable Signed Distance Functions

Signed Distance Function - an overview

Gene Chou, Ilya Chugunov, Felix Heide

[6th Jun., 2022] [arXiv 2022]

[Paper]

Learning a Joint Occupancy, Signed Distance, and Normal Field for Shape Representation

Nikolas Lamb, Sean Banerjee, Natasha Kholgade Banerjee

[22th Nov., 2022] [SIGGRAPH Asia 2022 ]

[Paper]

Master Thesis Statistical Shape Models with Signed Distance Functions

Steiner

[01st Jan., 2019] [PDF, 2019]

[Paper]

RoCoSDF: Row-Column Scanned Neural Signed Distance Fields for Freehand Ultrasound 3D Shape Reconstruction

Hongbo Chen, Yuchong Gao, Ruihua Zhang, Benjamin Van Roy, Lu Fang

[01st Sep., 2024] [MICCAI, 2024]

[Paper]

2.Medical anatomical shape modeling and geometric mesh reconstruction (heart/blood vessels/bones/organs, etc.)

Large Intestine 3D Shape Refinement Using Conditional Latent Point Diffusion Models

Kaouther Mouheb, Mobina Ghojogh Nejad, Lavsen Dahal, Ehsan Samei, Kyle J. Lafata, W. Paul Segars, Joseph Y. Lo

[15th Sep., 2023] [arXiv 2023]

[Paper]

3D organ shape reconstruction from Topogram images

Elena Balashova, Jiangping Wang, Vivek Singh, Bogdan Georgescu, Brian Teixeira, Ankur Kapoor

[29th Mar., 2019] [arXiv 2019]

[Paper]

AnatomyGen: deep anatomy generation from dense representation with applications in mandible synthesis

Amir H. Abdi, Heather Borgard, Purang Abolmaesumi, Sidney Fels

[28th Feb., 2019] [MIDL 2019]

[Paper]

Methodology of generation of CFD meshes and 4D shape reconstruction of coronary arteries from patient-specific dynamic CT.

Krzysztof Psiuk-Maksymowicz, Damian Borys, Bartlomiej Melka, Maria Gracka, Wojciech P. Adamczyk

[25th Jan., 2024] [Scientific Reports 2024]

[Paper]

3D shape reconstruction of the femur from planar X-ray images using statistical shape and appearance models.

D Nolte, S Xie, AMJ Bull

[24th Mar., 2023] [[BioMedical Engineering OnLine 2023]

[Paper]

Synthesis of realistic subcortical anatomy with known surface deformations

Yi Gao ,Sylvain Bouix

[25th Jan., 2012] [MICCAI 2012 ]

[Paper]

Shape registration with learned deformations for 3D shape reconstruction from sparse and incomplete point clouds.

X Chen, N Ravikumar, Y Xia, R Attar, A Diaz-Pinto, SK Piechnik, S Neubauer, SE Petersen

[22th Dec., 2021] [Medical Image Analysis 2021]

[Paper]

Aortic Valve Leaflet Shape Synthesis With Geometric Prior From Surrounding Tissue

Jannis Hagenah, Michael Scharfschwerdt, Floris Ernst

[9th Mar., 2022] [Frontiers in Cardiovascular Medicine 2022]

[Paper]

Implicit Neural Representations for Generative Modeling of Living Cell Shapes

Tongue shape synthesis based on Active Shape Model

David Wiesner, Julian Suk, Sven Dummer, David Svoboda, Jelmer M. Wolterink

[6th Oct., 2022] [MICCAI 2022]

[Paper]

Geometric analysis of shapes and its application to medical image analysis.

A Mukhopadhyay

[6th Oct., 2022] [MICCAI 2022]

[Paper]

UNSURF: Uncertainty Quantification for Cortical Surface Reconstruction of Clinical Brain MRIs

Raghav Mehta, Karthik Gopinath, Ben Glocker, Juan Eugenio Iglesias

[2014] [Journal (unspecified)]

[Paper]

A Survey of Deep Learning Approaches for Medical Image-to-Mesh Reconstruction

Fengming Lin, Arezoo Zakeri, Yidan Xue, Michael MacRaild, Haoran Dou, Zherui Zhou, Ziwei Zou, Ali Sarrami-Foroushani, Jinming Duan, Alejandro F. Frangi

[6th May., 2025] [arXiv 2025]

[Paper]

Image-To-Mesh Conversion for Biomedical Simulations

Fotis Drakopoulos, Kevin Garner, Christopher Rector, Nikos Chrisochoides

[27th Feb., 2024] [arXiv 2024]

[Paper]

Lightweight triangular mesh deformable reconstruction for low-resolution and roughly segmented 3D medical images

Hongkai Yu, Guoying Hao, Yibo Gao

[01st Sep., 2025] [ScienceDirect, 2025]

[Paper]

Enhanced Algorithm for Reconstruction of Three-Dimensional Mesh Models from Medical Images for Deep Learning

Authors not specified

[01st Dec., 2020] [SAI, 2020]

[Paper]

Delaunay Mesh Reconstruction from 3D Medical Images Based on Centroidal Voronoi Tessellation

Authors not specified

[01st Jan., 2009] [IEEE, 2009]

[Paper]

A deep-learning approach for direct whole-heart mesh reconstruction

Feng Hou, Benjamin A Watson, Yan Xia, Yu-Wei Wu, Hao Shen, Yan-Jie Zhou, Hong-Quan Kou, Cheng Zhong, Yu-Jie Chen, Lei Xu, Jing-Jing Xiao, Hualin Qiao, Shu-Sheng Li, You-Yi Zheng, Dinggang Shen, Li Wang

[01st Sep., 2021] [PMC, 2021]

[Paper]

Advanced 3D Mesh Generation from 2D Images in Python

Authors not specified

[16th Feb., 2024] [Medium, 2024]

[Paper]

Neuronal Mesh Reconstruction from Image Stacks Using Implicit Neural Representations

Jingtan Li, Hongkun Yu, Shengtao Lv, Xi Chen

[01st Apr., 2025] [MDPI, 2025]

[Paper]

3D reconstruction from multiple images

Authors not specified

[01st Jan., 2023] [Wikipedia, 2023]

[Paper]

Dense 3D organ modeling from a laparoscopic video

Authors not specified

[20th Apr., 2021] [SPIE, 2021]

[Paper]

From 2D to 3D, Deep Learning-based Shape Reconstruction in Magnetic Resonance Imaging: A Review

Authors not specified

[01st Oct., 2025] [arXiv, 2025]

[Paper]

Survey of methods and principles in three-dimensional reconstruction from two-dimensional medical images

Yong Xia, Yang Zhou

[27th Jul., 2023] [PMC, 2023]

[Paper]

PRISM: Probabilistic Representation for Integrated Shape Modeling

Yiming Wu, Zhenhua Wu, Bingfeng Zhou, Yongcai Guo

[06th Apr., 2025] [arXiv, 2025]

[Paper]

DeepSSM: A blueprint for image-to-shape deep learning models

Riddhish Bhalodia, Shireen Y Elhabian, Ladislav Kavan, Ross T Whitaker

[01st Sep., 2023] [ScienceDirect, 2023]

[Paper]

Generative deep learning furthers the understanding of local distributions of fat and muscle on body shape and health using 3D surface scans

Yannik Erbslöh, Zachary T Ward, Sophie Chabloz, Eva Kwofie, Anna J Schult, Amir Vahid, Charles C Bell, Alejandro Bertolet, Gregory S Patience, Samuel Y Paik, Michael C Kampffmeyer, Alexander M Ehlers, Knut Matre, Line Eikvil, Jennifer Linge, Sharath Kandambeth, Olof Dahlqvist Leinhard, Thorkild IA Sørensen, Gary P Liney, Jennifer Lyn Baker

[30th Jan., 2024] [PubMed, 2024]

[Paper]

Steerable Anatomical Shape Synthesis with Implicit Neural Representations

Florian Hartmann, Stephen Sinclair, Bernhard Kerbl, Markus Steinberger

[04th Apr., 2025] [arXiv, 2025]

[Paper]

Generative modeling of the Circle of Willis using 3D-StyleGAN

Javid Dadashkarimi, Amin Golzari Oskouei, Qinghao Liang, Amani Valestino, Sina Sadeghzadeh, Arash Nazeri, Yasin Ibrahim, Mohammad Amin Sadeghi, Amin Oskooei, Farhad R Nezami, Ameer E Hassan, Claudio Chavarrias, Seyyed A Hosseini, Adnan I Qureshi, Ramin Zand, Paul A Yushkevich, Farshid Sepehrband

[15th Dec., 2024] [ScienceDirect, 2024]

[Paper]

Explainable Anatomical Shape Analysis through Deep Hierarchical Generative Models

Carlo Biffi, Juan J Cerrolaza, Giacomo Tarroni, Wenjia Bai, Ozan Oktay, Loic Le Folgoc, Konstantinos Kamnitsas, Antonio de Marvao, Georgia Doumou, Jinming Duan, Sanjay K Prasad, Stuart A Cook, Declan P O'Regan, Daniel Rueckert

[01st Jun., 2020] [PMC, 2020]

[Paper]

Generative modeling of biological shapes and images using a probabilistic α-shape sampler

Kristin Branson, Alice A Robie, Michael J Reiser, David M Stern

[11th Jan., 2024] [bioRxiv, 2024]

[Paper]

3.3D/4D temporal medical image generation and diffusion model (including controllable generation)

Denoising diffusion probabilistic models for 3D medical image generation

Firas Khader, Gustav Mueller-Franzes, Soroosh Tayebi Arasteh, Tianyu Han, Christoph Haarburger, Maximilian Schulze-Hagen, Philipp Schad, Sandy Engelhardt, Bettina Baessler, Sebastian Foersch, Johannes Stegmaier, Christiane Kuhl, Sven Nebelung, Jakob Nikolas Kather, Daniel Truhn

[3th Jan., 2023] [arXiv, 2023]

[Paper]

Tumor Synthesis Conditioned on Radiomics

Jonghun Kim, Inye Na, Eun Sook Ko, Hyunjin Park

[29th Sep., 2025] [WACV, 2025]

[Paper]

Realistic lung nodule synthesis with multi-target co-guided adversarial mechanism

Q Wang, X Zhang, W Zhang, M Gao, S Huang, J Wang, J Zhang, D Yang, C Liu

[Sept., 2021] [IEEE Transactions on Medical Imaging, 2021]

[Paper]

Brain Imaging Generation with Latent Diffusion Models

Walter H. L. Pinaya, Petru-Daniel Tudosiu, Jessica Dafflon, Pedro F da Costa, Virginia Fernandez, Parashkev Nachev, Sebastien Ourselin, M. Jorge Cardoso

[15th Sep., 2022] [MICCAI 2022]

[Paper]

Simulation and synthesis in medical imaging

Can Zhao, David Svoboda, Jelmer M. Wolterink, Maria Escobar

[18th Sep., 2022] [SASHIMI 2022 / MICCAI Workshop, 2022]

[Paper]

Super-resolution of 3D medical images by generative adversarial networks with long and short-term memory and attention.

Qiong Zhang, Yiliu Hang, Fang Wu, Shentao Wang , Yue Hong

[1st Jul., 2025] [Scientific Reports, 2025]

[Paper]

Adaptive Latent Diffusion Model for 3D Medical Image to Image Translation: Multi-modal Magnetic Resonance Imaging Study

Jonghun Kim, Hyunjin Park

[1st Nov., 2023] [MACV 2024]

[Paper]

3D-DGGAN: A Data-Guided Generative Adversarial Network for High Fidelity in Medical Image Generation.

Jion Kim,Yan Li,Byeong-Seok Shin

[May, 2024] [IEEE Journal of Biomedical and Health Informatics, 2024]

[Paper]

Inflating 2D convolution weights for efficient generation of 3D medical images.

Yanbin Liu, Girish Dwivedi, Farid Boussaid, Frank Sanfilippo, Makoto Yamada, Mohammed Bennamoun

[5th Dec.,2023] [CMPB, 2023]

[Paper]

Enhancing adaptive proton therapy through CBCT images: Synthetic head and neck CT generation based on 3D vision transformers.

D Viar‐Hernandez, JM Molina‐Maza, JA Vera‐Sánchez, JM Perez‐Moreno, A Mazal

[1st Apr.,2024] [Medical Physics, 2024]

[Paper]

Persistence Image from 3D Medical Image: Superpixel and Optimized Gaussian Coefficient

Yanfan Zhu, Yash Singh, Khaled Younis, Shunxing Bao, Yuankai Huo

[15th Aug.,2024] [arXiv, 2024]

[Paper]

3D MedDiffusion: A 3D Medical Diffusion Model for Controllable and High-Quality Medical Image Generation

Yingying Song, Haixin Luo, Liyue Shen

[17th Dec., 2024] [arXiv, 2024]

[Paper]

Computationally Efficient Diffusion Models in Medical Imaging: A Comprehensive Review

Abdullah, Tao Huang, Ickjai Lee, Euijoon Ahn

[09th May, 2025] [arXiv, 2025]

[Paper]

OctFusion: Octree-based Diffusion Models for 3D Shape Generation

Biao Zhang, Jiapeng Tang, Matthias Niessner, Peter Wonka

[27th Aug., 2024] [arXiv, 2024]

[Paper]

MAISI-v2: Accelerated 3D High-Resolution Medical Image Synthesis with Cascade Diffusion Models

Guan Wang, Hongkai Yu, Mengzhou Li, Jiajun Sun, Jie Chu, Aaron Fenster, Yibo Gao

[12th Aug., 2024] [arXiv, 2024]

[Paper]

XReal: Realistic Anatomy and Pathology-Aware X-ray Generation via Controllable Diffusion Model

Xu Han, Yifeng Xiong, Zhiqi Li, Wenhui Lei, Jingfeng Yao, Yan Xi, Ningitao Zhang, Xiaokun Liang, Qingle Wang, Xiaojiang Yang, Junwei Han, Yueh Z. Lee, Jianfeng Xu

[14th Mar., 2024] [arXiv, 2024]

[Paper]

LesionDiffusion: Towards Text-controlled General Lesion Synthesis

Peng Zheng, Zhonggan Ding, Dengwen Zhou, Jiongquan Chen, Huizhu Jia, Kunchang Li, Yanyu Xu, Anhan Liu, Yefei Wang, Shiqi Wang

[02nd Mar., 2025] [arXiv, 2025]

[Paper]

Med-cDiff: Conditional Medical Image Generation with Diffusion Models

Guillermo Iglesias, Edgar Rangel, Gisela Mayer-Wolf, Christian Baumgartner

[01st Nov., 2023] [PMC, 2023]

[Paper]

SADIR: Shape-Aware Diffusion Models for 3D Image Reconstruction

Nurie Kim, Soon Hyung Pyo, Ho Yun Lee, Ho Young Lee, Sunghyun Cho

[01st Mar., 2023] [PMC, 2023]

[Paper]

Probing the limits and capabilities of diffusion models for generating realistic 3D medical images

Gustav Müller-Franzes, Jan Nikolas Morshuis, Jens Kleesiek, Christian F. Baumgartner

[05th Dec., 2024] [Nature, 2024]

[Paper]

3D Shape-to-Image Brownian Bridge Diffusion for Brain MRI Synthesis

Yuhang Huang, Weijian Huang, Evangelos Kalogerakis

[18th Feb., 2025] [arXiv, 2025]

[Paper]

Window projection with Bayesian diffusion for 3D shape reconstruction from sparse view images

Yueci Deng, Jiahao Lu, Jiawei Mo, Yipeng Qin, Xiaokang Wang, Xiaoyang Huang, Jiancheng Lv, Joachim M Buhmann

[01st Sep., 2025] [ScienceDirect, 2025]

[Paper]

Diffusion Deformable Model for 4D Temporal Medical Image Generation

Boah Kim, Jong Chul Ye

[27th Jun., 2022] [arXiv, 2022]

[Paper]

Controllable Mask Diffusion Model for medical annotation synthesis

Xiang Jiang, Xiaomeng Li, Wenlong Liao, Liyang Chen, Xinqi Liu, Quan Quan, Rongsheng Wang, Shen Zhao, Chaoyi Wu, Li Lin, Hao Chen

[01st Nov., 2025] [ScienceDirect, 2025]

[Paper]

LeFusion: Controllable Pathology Synthesis via Lesion-Focused Diffusion Models

Zheyun Qin, Yi Lin, Huifeng Yao, Xiaomeng Li

[01st Jan., 2024] [OpenReview, 2024]

[Paper]

Anatomically-Controllable Medical Image Generation with Segmentation-Guided Diffusion Models

Yue Zhao, Xiaokun Liang, Di Liu, Junwei Yang, Jiajie Jin, Hanwu Chen, Han Liu, Pheng-Ann Heng, Zaiyi Liu, Lingjie Liu

[07th Oct., 2024] [ACM, 2024]

[Paper]

A 3D Medical Latent Diffusion Model for Controllable and High-Quality Medical Image Generation

Yingying Song, Haixin Luo, Liyue Shen

[01st Sep., 2024] [ResearchGate, 2024]

[Paper]

Generative Models for Synthesizing Anatomical Plausible 3D Medical Images

Authors not specified

[14th Sep., 2025] [ResearchGate, 2025]

[Paper]

Generative Enhancement for 3D Medical Images

Lingting Zhu, Noel Codella, Dongdong Chen, Zhenchao Jin, Lu Yuan, Lequan Yu

[24th May., 2024] [arXiv, 2024]

[Paper]

Learning Neural Deformation Representation for 4D Dynamic Shape Generation

Boyao Zhou, Ruixi Ma, Yida Wang, Kai Xu, Huamin Wang

[18th Sep., 2024] [ECCV, 2024]

[Paper]

Patient-specific deep learning model to enhance 4D-CBCT image for radiomics analysis

Ziyuan Wang, Thomas C Harris, Yin Gao, Panagiotis Tsirigotis, Tan Nguyen, Amber Cutler, Ming Chao, Dan Nguyen, Steve B Jiang

[06th May, 2022] [PMC, 2022]

[Paper]

Transfer-learning is a key ingredient to fast deep learning-based 4D liver MRI reconstruction

OuYang Cheng, Qiegen Liu, Jun Lv, Kaining Ying, Hao Chen, Tao Tan, Hairong Zheng, Dong Liang, Shanshan Wang

[11th Jul., 2023] [Nature, 2023]

[Paper]

Statistical 3D and 4D Shape Analysis: Theory and Applications in Medical Imaging

Fernando Arce, Ellen Gasparovic, Carola Wenk

[01st Nov., 2024] [Murdoch, 2024]

[Paper]

Exploring deep learning models for 4D-STEM-DPC data processing

Zhongbo Li, Vivekanand Murlidhar, Yi Jiang

[15th Mar., 2024] [ScienceDirect, 2024]

[Paper]

3dMD Announces the Next Generation of Downstream Dynamic-4D Shape Generation Tools

Authors not specified

[10th Apr., 2024] [3dMD, 2024]

[Paper]

Super-resolution of 3D medical images by generative adversarial networks with dual perceptual losses

Yingying Zhu, Jianmin Jiang, Yongliang Wang

[01st Jul., 2025] [Nature, 2025]

[Paper]

Controllable Counterfactual Generation for Interpretable Medical Image Classification

Shengjia Chen, Yijun Yang, Chih-Hui Ho, Yu-Cheng Chang, Jen-Tse Dong, Wei-Chen Chiu, Yen-Yu Lin

[01st Oct., 2024] [MICCAI, 2024]

[Paper]

Med3DVLM: An Efficient Vision-Language Model for 3D Medical Image Analysis

Yu Xin, Gorkem Can Ates, Kuang Gong, Wei Shao

[15th Aug., 2025] [arXiv 2025]

[Paper]

MedM-VL: What Makes a Good Medical LVLM?

Yiming Shi, Shaoshuai Yang, Xun Zhu, Haoyu Wang, Xiangling Fu, Miao Li, Ji Wu

[12th Sep., 2025] [arXiv 2025]

[Paper]

Multi-Modal Understanding and Generation for Medical Images and Text via Vision-Language Pre-Training

Jong Hak Moon, Hyungyung Lee, Woncheol Shin, Young-Hak Kim, Edward Choi

[21th Sep., 2022] [arXiv 2022]

[Paper]

3D-CT-GPT: Generating 3D Radiology Reports through Integration of Large Vision-Language Models

Hao Chen, Wei Zhao, Yingli Li, Tianyang Zhong, Yisong Wang, Youlan Shang, Lei Guo, Junwei Han, Tianming Liu, Jun Liu, Tuo Zhang

[28th Sep., 2024] [arXiv 2024]

[Paper]

A vision attention driven Language framework for medical report generation.

Merve Varol Arısoy, Ayhan Arısoy , İlhan Uysal

[28th Mar., 2025] [scientific reports 2025]

[Paper]

Abn-BLIP: Abnormality-aligned Bootstrapping Language-Image Pre-training for Pulmonary Embolism Diagnosis and Report Generation from CTPA

Zhusi Zhong, Yuli Wang, Lulu Bi, Zhuoqi Ma, Sun Ho Ahn, Christopher J. Mullin, Colin F. Greineder, Michael K. Atalay, Scott Collins, Grayson L. Baird, Cheng Ting Lin, Webster Stayman, Todd M. Kolb, Ihab Kamel, Harrison X. Bai, Zhicheng Jiao

[12th Nov., 2025] [arXiv 2025]

[Paper]

From vision to text: A comprehensive review of natural image captioning in medical diagnosis and radiology report generation.

Gabriel Reale-Nosei , Elvira Amador-Domínguez ,Emilio Serrano

[Medical Image Analysis, 2024]

[Paper]

M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language Models

Fan Bai, Yuxin Du, Tiejun Huang, Max Q.-H. Meng, Bo Zhao

[31th Mar., 2024] [arXiv 2024]

[Paper]

Med-2E3: A 2D-Enhanced 3D Medical Multimodal Large Language Model

Yiming Shi, Xun Zhu, Kaiwen Wang, Ying Hu, Chenyi Guo, Miao Li, Ji Wu

[21th Oct., 2025] [arXiv 2025]

[Paper]

Unified Medical Image Pre-training in Language-Guided Common Semantic Space

Xiaoxuan He, Yifan Yang, Xinyang Jiang, Xufang Luo, Haoji Hu, Siyun Zhao, Dongsheng Li, Yuqing Yang, Lili Qiu

[4th Jul., 2024] [arXiv 2024]

[Paper]

Vision, body and interpretation in medical imaging diagnostics

Renzhen Chen , Jan Kyrre Berg Olsen Friis

[4th Apr., 2024] [Medicine, Health Care and Philosophy, 2024]

[Paper]

4.Medical image segmentation/classification with Transformer/Mamba/CNN

SAM-Med3D: A Vision Foundation Model for General-Purpose Segmentation on Volumetric Medical Images.

Haoyu Wang, Sizheng Guo, Jin Ye, Zhongying Deng, Junlong Cheng, Tianbin Li, Jianpin Chen, Yanzhou Su, Ziyan Huang, Yiqing Shen, Bin Fu, Shaoting Zhang, Junjun He, Yu Qiao

[14th Sep., 2024] [arXiv, 2024]

[Paper]

3D marker-controlled watershed for kidney segmentation in clinical CT exams

W Wieclawek

[27th Feb., 2018] [Biomedical engineering online, 2018]

[Paper]

Few-Shot Adaptation of Training-Free Foundation Model for 3D Medical Image Segmentation

Xingxin He, Yifan Hu, Zhaoye Zhou, Mohamed Jarraya, Fang Liu

[15th Jan., 2025] [arXiv, 2025]

[Paper]

VM-UNet: Vision Mamba UNet for Medical Image Segmentation

Jiacheng Ruan, Jincheng Li, Suncheng Xiang

[8th Nov., 2024] [arXiv, 2024]

[Paper]

SegMamba: Long-Range Sequential Modeling Mamba for 3D Medical Image Segmentation

Zhaohu Xing, Tian Ye, Yijun Yang, Guang Liu, Lei Zhu

[15th Sep., 2024] [arXiv, 2024]

[Paper]

UNETR: Transformers for 3D Medical Image Segmentation

Ali Hatamizadeh, Yucheng Tang, Vishwesh Nath, Dong Yang, Andriy Myronenko, Bennett Landman, Holger Roth, Daguang Xu

[9th Oct., 2021] [MACV, 2022]

[Paper]

Slim UNETR++: A lightweight 3D medical image segmentation network for medical image analysis.

Jiawei Jin, Sen Yang, Jigang Tong, Kai Zhang ,Zenghui Wang

[2nd Jun., 2025] [Medical & Biological Engineering & Computing, Vol.63, 2025]

[Paper]

TDFormer: Top-Down Token Generation for 3D Medical Image Segmentation.

Hao Du, Qihua Dong,Yan Xu,Jing Liao

[Oct., 2025] [IEEE Journal of Biomedical and Health Informatics, 2025]

[Paper]

Grouped multi-scale vision transformer for medical image segmentation.

Z Ji, Z Chen, X Ma

[1st Apr.,2025] [Scientific Reports, 2025]

[Paper]

MedViT: A robust vision transformer for generalized medical image classification

Omid Nejati Manzari, Hamid Ahmadabadi, Hossein Kashiani, Shahriar B. Shokouhi, Ahmad Ayatollahi

[19th Feb., 2023] [arXiv, 2023]

[Paper]

Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysis

Yucheng Tang, Dong Yang, Wenqi Li, Holger Roth, Bennett Landman, Daguang Xu, Vishwesh Nath, Ali Hatamizadeh

[28th Mar., 2022] [CVPR, 2023]

[Paper]

Medical Image Segmentation with 3D Convolutional Neural Networks: A Survey

S Niyas, S J Pawan, M Anand Kumar, Jeny Rajan

[28th Apr., 2022] [arXiv 2022]

[Paper]

Masked Image Modeling Advances 3D Medical Image Analysis

Zekai Chen, Devansh Agarwal, Kshitij Aggarwal, Wiem Safta, Samit Hirawat, Venkat Sethuraman, Mariann Micsinai Balan, Kevin Brown

[25th Apr., 2022] [MACV 2023]

[Paper]

Adapting Pre-trained Vision Transformers from 2D to 3D through Weight Inflation Improves Medical Image Segmentation

Yuhui Zhang, Shih-Cheng Huang, Zhengping Zhou, Matthew P. Lungren, Serena Yeung

[8th Feb., 2022] [ML4H 2022]

[Paper]

MobileViM: A Light-weight and Dimension-independent Vision Mamba for 3D Medical Image Analysis

Wei Dai, Jun Liu

[19th Feb., 2025] [arXiv 2025]

[Paper]

Vision Mamba and xLSTM-UNet for medical image segmentation.

Xin Zhong, Gehao Lu ,Hao Li

[10th Mar.,2025] [scientific reports, 2025]

[Paper]

General lightweight framework for vision foundation model supporting multi-task and multi-center medical image analysis.

Senliang Lu, Yehang Chen, Yuan Chen, Peijun Li, Junqi Sun, Changye Zheng, Yujian Zou, Bo Liang, Mingwei Li, Qinggeng Jin, Enming Cui, Wansheng Long ,Bao Feng

[1st Mar.,2025] [nature communications, 2025]

[Paper]

TTT-Vnet: a 3D vision test-time training model for medical image analysis

Shaoyan Pan, Vanessa Su, Shaoyuan Lo, Mingzhe Hu, Yuheng Li, Chih-Wei Chang, Tonghe Wang, Richard Qiu, Xiaofeng Yang

[11th Apr.,2025] [Medical Imaging 2025]

[Paper]

5.Applications and Overview of Transformer/ViT in Medical Imaging

Advances in medical image analysis with vision Transformers: A comprehensive review

Reza Azad, Amirhossein Kazerouni, Moein Heidari, Ehsan Khodapanah Aghdam, Amirali Molaei, Yiwei Jia, Abin Jose, Rijo Roy, Dorit Merhof

[5th Nov., 2023] [arXiv 2023]

[Paper]

Transformers in medical image analysis

Kelei He, Chen Gan, Zhuoyuan Li, Islem Rekik, Zihao Yin, Wen Ji, Yang Gao, Qian Wang, Junfeng Zhang, Dinggang Shen

[19th Aug., 2022] [arXiv 2022]

[Paper]

Comparison of Vision Transformers and Convolutional Neural Networks in Medical Image Analysis: A Systematic Review

S Takahashi, Y Sakaguchi, N Kouno, K Takasawa, K Ishizu, Y Akagi, R Aoyama, N Teraya

[12th Sep., 2024] [Journal of Medical Systems, 2024]

[Paper]

Artificial General Intelligence for Medical Imaging Analysis

Xiang Li, Lin Zhao, Lu Zhang, Zihao Wu, Zhengliang Liu, Hanqi Jiang, Chao Cao, Shaochen Xu, Yiwei Li, Haixing Dai, Yixuan Yuan, Jun Liu, Gang Li, Dajiang Zhu, Pingkun Yan, Quanzheng Li, Wei Liu, Tianming Liu, Dinggang Shen

[21th Nov., 2024] [arXiv 2024]

[Paper]

6. 3D Shape Generation, Datasets, and Reviews (General + Medical)

3D Representation Methods: A Survey

Zhengren Wang

[9th Oct., 2024] [arXiv 2024]

[Paper]

MedShapeNet – a large-scale dataset of 3D medical shapes for computer vision

Jianning Li, Zongwei Zhou, Jiancheng Yang, Antonio Pepe, Christina Gsaxner, Gijs Luijten, Chongyu Qu, Tiezheng Zhang, Xiaoxi Chen, Wenxuan Li, Marek Wodzinski, Paul Friedrich, Kangxian Xie, Yuan Jin, Narmada Ambigapathy, Enrico Nasca, Naida Solak, Gian Marco Melito, Viet Duc Vu, Afaque R. Memon

[12th Dec., 2023] [arXiv 2023]

[Paper]

3D Deep Learning on Medical Images: A Review

Satya P. Singh, Lipo Wang, Sukrit Gupta, Haveesh Goli, Parasuraman Padmanabhan, Balázs Gulyás

[13th Oct., 2020] [arXiv 2020]

[Paper]

Cardiovascular Medical Image and Analysis based on 3D Vision: A Comprehensive Survey

Zhifeng Wang, Renjiao Yi, Xin Wen, Chenyang Zhu, Kai Xu

[2024] [Meta-Radiology, 2024]

[Paper]

Diffusion models for 3D generation: A survey

Ziyi Wu, Yaoyi Li, Xiping Hu, Zhongyuan Wang, Hujun Bao

[28th Feb., 2025] [SciOpen, 2025]

[Paper]

3D Brain and Heart Volume Generative Models: A Survey

Yanbin Gong, Weizhan Zhang, Kaicong Sun, Xiangyu Yue, Hao Chen, Jie Li, Haiping Zhu

[11th Oct., 2022] [arXiv, 2022]

[Paper]

Generative Artificial Intelligence in Medical Imaging: Foundations, Progress, and Clinical Translation

Xuanru Zhou, Cheng Li, Shuqiang Wang, Ye Li, Tao Tan, Hairong Zheng, Shanshan Wang

[13th Aug., 2025] [arXiv, 2025]

[Paper]

7.Medical basic network/model training techniques (ViT general pre-training, etc.)

FastSAM-3DSlicer: A 3D-Slicer Extension for 3D Volumetric Segment Anything Model with Uncertainty Quantification

Yiqing Shen, Xinyuan Shao, Blanca Inigo Romillo, David Dreizin, Mathias Unberath

[17th Jul., 2024] [arXiv, 2024]

[Paper]

VELVET-Med: Vision and Efficient Language Pre-training for Volumetric Imaging Tasks in Medicine

Ziyang Zhang, Yang Yu, Xulei Yang, Si Yong Yeo

[16th Aug., 2025] [arXiv, 2025]

[Paper]

Self-supervised anomaly detection with random-shape pseudo-outliers

Hanqiu Deng,Xingyu Li

[15th Jul.,2022] [EMBC 2022]

[Paper]

8.3D Reconstruction of Natural Scenes / 3D Printing and Clinical Applications

MonoSelfRecon: Purely Self-Supervised Explicit Generalizable 3D Reconstruction of Indoor Scenes from Monocular RGB Views

Runfa Li, Upal Mahbub, Vasudev Bhaskaran, Truong Nguyen

[10th Apr., 2024] [arXiv, 2024]

[Paper]

Structure-aware shape synthesis

Elena Balashova, Vivek Singh, Jiangping Wang, Brian Teixeira, Terrence Chen, Thomas Funkhouser

[4th Aug., 2018] [arXiv, 2018]

[Paper]

Task-Aware 3D Geometric Synthesis

Sellán, Silvia

[2024] [PhD Dissertation, University of Toronto, 2024]

[Paper]

A generative shape compositional framework to synthesize populations of virtual chimeras

Haoran Dou, Seppo Virtanen, Nishant Ravikumar, Alejandro F. Frangi

[4th Oct., 2022] [arXiv, 2022]

[Paper]

Creating and Reenacting Controllable 3D Humans with Differentiable Rendering

Chuan Guo, Tianjian Jiang, Xu Chen, Jie Song, Otmar Hilliges

[22nd Oct., 2021] [arXiv, 2021]

[Paper]

DreamDPO: Aligning Text-to-3D Generation with Human Preference

Shentong Mo, Tianyu Yang, Zhan Li, Jingjing Ren, Enze Xie, Wenyi Mo, Zhixin Lin, Dongdong Chen, Ming Yang

[05th Feb., 2025] [arXiv, 2025]

[Paper]

Application of artificial intelligence in 3D printing physical organ models

Jing Yang, Jinjin Zheng

[01st Sep., 2023] [ScienceDirect, 2023]

[Paper]

Generative AI for medical 3D printing: a comparison of ChatGPT outputs to reference standard education for selected additive manufacturing applications

Helen Xun, David Chen, Paul P Petit, Jason S Naftulin, Beau M Hokensen, Christian Park, Raj M Amin, Dawn M Laporte

[01st Aug., 2023] [BMC, 2023]

[Paper]

Multimodal generative AI for interpreting 3D medical images and medical videos

Michael Moor, Qian Huang, Shirley Ren, Michihiro Yasunaga, Cyril Zakka, Jacob R Blum, Canwen Xu, Cyrus Rashtchian, Pranav Rajpurkar, Michael A Pfeffer

[13th May, 2025] [PMC, 2025]

[Paper]

9.Point cloud / Statistical shape / Point cloud diffusion and completion

Multi-class point cloud completion networks for 3D cardiac anatomy reconstruction from cine magnetic resonance images

Thomas Joyce, Francesca Galassi, Stefano Buoso, Benedetta Biffi, Sebastian Kozerke, Anastasia Dubrovina

[01st Sep., 2023] [ScienceDirect, 2023]

[Paper]

Med-PU: Point Cloud Upsampling for High-Fidelity 3D Medical Shape Reconstruction

Jianning Li, Moon Kim, Antonio Pepe, Christina Schwarz-Gsaxner, Jens Kleesiek, Jan Egger

[28th Sep., 2025] [arXiv, 2025]

[Paper]

Can point cloud networks learn statistical shape models of anatomies?

Jadie Adams, Shireen Y Elhabian

[01st Oct., 2023] [PMC, 2023]

[Paper]

Hierarchical Feature Learning for Medical Point Clouds via State Space Models

Shuquan Ye, Dongdong Chen, Jiaming Sun, Jingyu Liu, Yu-Gang Jiang, Xiaohong Liu, Yixuan Yuan

[17th Apr., 2025] [arXiv, 2025]

[Paper]

A MedShapeNet Foundation Model - Learning-Based Multimodal Medical Point Cloud Completion

Jianning Li, Antonio Pepe, Christina Schwarz-Gsaxner, Jens Kleesiek, Jan Egger

[16th Oct., 2024] [ResearchGate, 2024]

[Paper]

3D cardiac shape analysis with variational point cloud autoencoders

Authors not specified

[01st Sep., 2025] [ScienceDirect, 2025]

[Paper]

Point Cloud Diffusion Models for Automatic Implant Generation

Paul Friedrich, Julia Wolleb, Florentin Bieder, Fisher Yu, Tim Finkenstädt, Victor Roux, Philippe C. Cattin

[01st Mar., 2023] [GitHub, 2023]

[Paper]

A conditional point cloud diffusion model for deformable liver motion modelling

Sihao Chen, Johan Brynolfsson, Tufve Nyholm, Tommy Löfstedt

[25th Jun., 2025] [PMC, 2025]

[Paper]

10.Skeleton, vascular tree, and topology (reconstruction/segmentation/generation)

Fast vascular skeleton extraction algorithm

Bogdan Belean, Monica Borda, Raul Malutan, Simona Barburiceanu

[01st Jun., 2016] [ScienceDirect, 2016]

[Paper]

Automated Generation of Directed Graphs from Vascular Segmentations

Kristin McLeod, Alfonso Martinez, Alejandro F Frangi

[01st Aug., 2015] [PMC, 2015]

[Paper]

A novel procedure for medial axis reconstruction of vessels from medical images

Michal Chlebiej, Krzysztof Hryniów

[15th Jun., 2024] [ScienceDirect, 2024]

[Paper]

Skeleton-based cerebrovascular quantitative analysis

Hao Chen, Chen Wei, Lei Wang, Haiyong Zeng, Hongtu Ma, Huafeng Liu, Dong Liang

[20th Dec., 2016] [BMC, 2016]

[Paper]

An Unsupervised Approach for Extraction of Blood Vessels from Fundus Images

Sukadeep Kour, Anupama Arora

[01st Nov., 2018] [PMC, 2018]

[Paper]

Techniques and Algorithms for Hepatic Vessel Skeletonization in Medical Images

Jia Jia, Zhitao Xiao, Lei Geng, Ying Zhang, Yanna Gu

[01st Apr., 2022] [MDPI, 2022]

[Paper]

Extraction of 3D Vascular Tree Skeletons Based on the Analysis of Positions Relationship

Zhongwen Li, Jiping Liu, Ruixu Liu

[01st Jan., 2005] [Springer, 2005]

[Paper]

A Review of Vessel Extraction Techniques and Algorithms

Authors not specified

[01st Jan., 2004] [SIUE, 2004]

[Paper]

Three dimensional skeletonization and symbolic description in vascular imaging

Authors not specified

[01st Apr., 2013] [HAL, 2013]

[Paper]

A recursive method for the extraction of vascular tree skeleton and application

Authors not specified

[01st Jan., 2018] [TSI, 2018]

[Paper]

Topology-aware reconstruction of thin tubular structures

Fabian Bongratz, Christoph Polzin, Daniel Cremers

[01st Nov., 2014] [ACM, 2014]

[Paper]

Topology-Aware Single-Image 3D Shape Reconstruction

Wei Chen, Haofeng Zhang, Qiong Wang, Hong Zhang, Congbo Cai, Jia Zheng

[01st Jun., 2020] [CVPRW, 2020]

[Paper]

Capturing Shape Information with Multi-Scale Topological Loss Terms for 3D Reconstruction

Dominik Bauer, Timothy D Barfoot

[03rd Mar., 2022] [arXiv, 2022]

[Paper]

Topology-Aware Focal Loss for 3D Image Segmentation

Andac Demir, Andrew Jesson, James Fishbaugh, Elizabeth Powell, Guido Gerig, Bulent Sankur

[24th Apr., 2023] [bioRxiv, 2023]

[Paper]

Topology-Preserving Shape Reconstruction and Registration via Neural Diffeomorphic Flow

Shanlin Sun, Kun Han, Deying Kong, Hao Tang, Xiangyi Yan, Xiaohui Xie

[01st Jun., 2022] [CVPR, 2022]

[Paper]

Topology-Aware Latent Diffusion for 3D Shape Generation

Jiangbei Hu, Yanggeng Li, Ben Fei, Jingyu Chen, Lei Zhang, Jianmin Zheng, Dong-Ming Yan

[01st Jan., 2024] [Semantic Scholar, 2024]

[Paper]