医学 AI

A Tutorial on MRI Reconstruction: From Modern Methods to Clinical Implications

Tolga Çukur, Salman U. H. Dar, Valiyeh Ansarian Nezhad, Yohan Jun, Tae Hyung Kim, Shohei Fujita, Berkin Bilgic

专题命中 医学影像 ：MRI(title,abstract)；diagnosis(abstract)；分类 eess.IV；biomedical(comments)

Comments Accepted for publication in IEEE Transactions on Biomedical Engineering. The final published version is available at https://doi.org/10.1109/TBME.2025.3617575

Mono-Modalizing Extremely Heterogeneous Multi-Modal Medical Image Registration

Kyobin Choo, Hyunkyung Han, Jinyeong Kim, Chanyong Yoon, Seong Jae Hwang

机构 * Department of Computer Science, Yonsei University（延世大学计算机科学系） ； Department of Artificial Intelligence, Yonsei University（延世大学人工智能系） ； Yonsei University College of Medicine（延世大学医学院） 纠错

专题命中 医学影像 ：medical image(title,comments)；MRI(abstract)；CT(abstract)；分类 cs.CV

Comments 11 pages, 3 figures, 2 tables, Accepted at Medical Image Computing and Computer Assisted Intervention (MICCAI) 2025

MvKeTR: Chest CT Report Generation with Multi-View Perception and Knowledge Enhancement

Xiwei Deng, Xianchun He, Jianfeng Bao, Yudan Zhou, Shuhui Cai, Congbo Cai, Zhong Chen

机构 * Institute of Artificial Intelligence, Xiamen University（厦门大学人工智能研究院） ； Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University（郑州大学第一附属医院磁共振成像科） ； Department of Electronic Science, Xiamen University（厦门大学电子科学系） 纠错

专题命中 医学影像 ：CT(title,abstract)；diagnosis(abstract)；分类 cs.CV；biomedical(comments)

Comments Accepted for publication in IEEE Journal of Biomedical and Health Informatics

Can Score-Based Generative Modeling Effectively Handle Medical Image Classification?

Sushmita Sarker, Prithul Sarker, George Bebis, Alireza Tavakkoli

专题命中 医学影像 ：medical image(title,abstract)；diagnosis(abstract)；分类 cs.CV；biomedical(comments)

Comments Accepted at the International Symposium on Biomedical Imaging (ISBI) 2025

Pretrained ViTs Yield Versatile Representations For Medical Images

Christos Matsoukas, Johan Fredin Haslum, Moein Sorkhei, Magnus Söderberg, Kevin Smith

专题命中 医学影像 ：medical image(title,abstract)；diagnosis(abstract,comments)；分类 cs.CV

Comments Extended version of arXiv:2108.09038 originally published at the ICCV 2021 Workshop on Computer Vision for Automated Medical Diagnosis

CUTS: A Deep Learning and Topological Framework for Multigranular Unsupervised Medical Image Segmentation

Chen Liu, Matthew Amodio, Liangbo L. Shen, Feng Gao, Arman Avesta, Sanjay Aneja, Jay C. Wang, Lucian V. Del Priore, Smita Krishnaswamy

专题命中 医学影像 ：medical image(title,abstract)；MRI(abstract)；分类 cs.CV

Comments Accepted to the 27th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2024)

Self-supervised Learning of Dense Hierarchical Representations for Medical Image Segmentation

Eytan Kats, Jochen G. Hirsch, Mattias P. Heinrich

专题命中 医学影像 ：medical image(title)；MRI(abstract)；CT(abstract)；分类 cs.CV

Comments Accepted for International Symposium on Biomedical Imaging 2024 (ISBI 2024)

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

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

专题命中 医学影像 ：medical image(title,abstract)；diagnosis(abstract)；分类 cs.CV

Comments MLLM, 3D medical image analysis

Self and Mixed Supervision to Improve Training Labels for Multi-Class Medical Image Segmentation

Jianfei Liu, Christopher Parnell, Ronald M. Summers

专题命中 医学影像 ：medical image(title,abstract)；CT(abstract)；分类 cs.CV；diagnosis(comments)

Comments 7 Pages, 3 figures, SPIE Medical Imaging 2024, Computer-aided diagnosis

Implicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts

Chenyu You, Weicheng Dai, Yifei Min, Lawrence Staib, James S. Duncan

专题命中 医学影像 ：medical image(title,abstract)；分类 cs.CV、cs.LG、eess.IV

Comments Accepted at International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2023)

Weakly Supervised 3D Classification of Chest CT using Aggregated Multi-Resolution Deep Segmentation Features

Anindo Saha, Fakrul I. Tushar, Khrystyna Faryna, Vincent M. D'Anniballe, Rui Hou, Maciej A. Mazurowski, Geoffrey D. Rubin, Joseph Y. Lo

专题命中 医学影像 ：CT(title,abstract)；diagnosis(abstract,comments)；分类 cs.CV

Comments Accepted to 2020 SPIE Medical Imaging: Computer-Aided Diagnosis [oral presentation]

Prediction of final infarct volume from native CT perfusion and treatment parameters using deep learning

David Robben, Anna M. M. Boers, Henk A. Marquering, Lucianne L. C. M. Langezaal, Yvo B. W. E. M. Roos, Robert J. van Oostenbrugge, Wim H. van Zwam, Diederik W. J. Dippel, Charles B. L. M. Majoie, Aad van der Lugt, Robin Lemmens, Paul Suetens

专题命中 医学影像 ：CT(title,abstract)；diagnosis(abstract)；分类 cs.CV；medical image(comments)

Comments Accepted for publication in Medical Image Analysis

Respiratory Motion Correction in Abdominal MRI using a Densely Connected U-Net with GAN-guided Training

Wenhao Jiang, Zhiyu Liu, Kit-Hang Lee, Shihui Chen, Yui-Lun Ng, Qi Dou, Hing-Chiu Chang, Ka-Wai Kwok

专题命中 医学影像 ：MRI(title,abstract)；diagnosis(abstract)；分类 eess.IV；medical image(comments)

Comments 8 pages, 4 figures, submitted to the 22nd International Conference on Medical Image Computing and Computer Assisted Intervention

Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images

Jo Schlemper, Ozan Oktay, Michiel Schaap, Mattias Heinrich, Bernhard Kainz, Ben Glocker, Daniel Rueckert

专题命中 医学影像 ：medical image(title,abstract)；CT(abstract)；分类 cs.CV

Comments Accepted for Medical Image Analysis (Special Issue on Medical Imaging with Deep Learning). arXiv admin note: substantial text overlap with arXiv:1804.03999, arXiv:1804.05338

Automatic brain tumor grading from MRI data using convolutional neural networks and quality assessment

Sergio Pereira, Raphael Meier, Victor Alves, Mauricio Reyes, Carlos A. Silva

专题命中 医学影像 ：MRI(title,abstract)；diagnosis(abstract)；分类 cs.CV；medical image(comments)

Comments Accepted and presented at iMIMIC - Workshop on Interpretability of Machine Intelligence in Medical Image Computing

Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning

Arnab Kumar Mondal, Jose Dolz, Christian Desrosiers

专题命中 医学影像 ：medical image(title,abstract)；MRI(abstract)；分类 cs.CV

Comments submitted to Medical Image Analysis for review

Unpaired Brain MR-to-CT Synthesis using a Structure-Constrained CycleGAN

Heran Yang, Jian Sun, Aaron Carass, Can Zhao, Junghoon Lee, Zongben Xu, Jerry Prince

专题命中 医学影像 ：CT(title,abstract)；medical image(abstract,comments)；分类 cs.CV

Comments 8 pages, 5 figures, accepted by MICCAI 2018 Workshop: Deep Learning in Medical Image Analysis (DLMIA)

Unsupervised Segmentation of 3D Medical Images Based on Clustering and Deep Representation Learning

Takayasu Moriya, Holger R. Roth, Shota Nakamura, Hirohisa Oda, Kai Nagara, Masahiro Oda, Kensaku Mori

专题命中 医学影像 ：medical image(title,abstract)；CT(abstract)；分类 cs.CV；biomedical(journal_ref)

Comments This paper was presented at SPIE Medical Imaging 2018, Houston, TX, USA

Journal ref Proc. SPIE 10578, Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging, 1057820 (12 March 2018)

A deep convolutional neural network using directional wavelets for low-dose X-ray CT reconstruction

Eunhee Kang, Junhong Min, Jong Chul Ye

专题命中 医学影像 ：CT(title,abstract)；diagnosis(abstract)；分类 cs.CV

Comments Will appear in Medical Physics (invited paper); 2016 AAPM low-dose CT Grand Challenge 2nd Place Award

RADNET: Radiologist Level Accuracy using Deep Learning for HEMORRHAGE detection in CT Scans

Monika Grewal, Muktabh Mayank Srivastava, Pulkit Kumar, Srikrishna Varadarajan

专题命中 医学影像 ：CT(title,abstract)；diagnosis(abstract)；分类 cs.CV；biomedical(comments)

Comments Accepted at IEEE Symposium on Biomedical Imaging (ISBI) 2018 as conference paper

Adversarial training and dilated convolutions for brain MRI segmentation

Pim Moeskops, Mitko Veta, Maxime W. Lafarge, Koen A. J. Eppenhof, Josien P. W. Pluim

专题命中 医学影像 ：MRI(title,abstract)；medical image(abstract,comments)；分类 cs.CV

Comments MICCAI 2017 Workshop on Deep Learning in Medical Image Analysis

Deep Learning for Multi-Task Medical Image Segmentation in Multiple Modalities

Pim Moeskops, Jelmer M. Wolterink, Bas H. M. van der Velden, Kenneth G. A. Gilhuijs, Tim Leiner, Max A. Viergever, Ivana Išgum

专题命中 医学影像 ：medical image(title,abstract)；MRI(abstract)；分类 cs.CV

Journal ref Moeskops, P., Wolterink, J.M., van der Velden, B.H.M., Gilhuijs, K.G.A., Leiner, T., Viergever, M.A., Išgum, I. Deep learning for multi-task medical image segmentation in multiple modalities. In: MICCAI 2016, pp. 478-486

Learning Deep Convolutional Features for MRI Based Alzheimer's Disease Classification

Fayao Liu, Chunhua Shen

专题命中 医学影像 ：MRI(title,abstract)；diagnosis(abstract)；分类 cs.CV

Comments This paper has been withdrawn by the author due to an error in the MRI data used in the experiments

A Predictive-Prescriptive Analytics Framework for Fair Computed Tomography Scheduling and Radiologist Workload Allocation

优化计算机断层扫描预约调度中的多利益相关方公平性：基于预测的扫描与报告时长

Ludovico Ambrosi, Chandra Bortolotto, Sara Cambiaghi, Luisa Carone, Davide Duma, Lorenzo Preda

专题命中 医学影像 ：CT(summary_cn,abstract)；radiology(abstract)

AI总结 本文针对CT随访调度中多利益相关方公平性缺失问题，提出预测-优化框架，结合ML模型与MILP模型，通过支配性约简策略提升效率，实验表明该方法可平衡患者需求与放射科医生工作量，XGBoost适配性最优。

PURe: A Plug-and-Play Product-Unit Residual Module for Vision Networks

PURe: 一种用于视觉网络的即插即用乘积单元残差模块

Ziyuan Li, Uwe Jaekel, Babette Dellen

机构 * Department of Mathematics, Informatics and Technology, University of Applied Sciences Koblenz（科隆应用科学大学数学、信息学与技术系） ； Technical University of Munich（慕尼黑技术大学） 纠错

专题命中 医学影像 ：CT(summary_cn,abstract)；分类 cs.CV、cs.LG、eess.IV

AI总结 提出PURe模块，通过二维乘积单元的对数域公式实现稳定的局部乘法交互，可替代残差网络中的标准单元，在图像分类和CT分割任务中提升精度-参数权衡。

Comments Accepted to the GCPR 2026

TumorBoard: Evidence-Grounded Multi-Agent Decision Support for Longitudinal Neuro-Oncology

TumorBoard：基于证据的多智能体纵向神经肿瘤学决策支持系统

Yantong Liu, Zheyu Zhang, Runpeng Liu, Mu Xitang, Seong-Yoon Shin, Hyun-Ae Lee

专题命中 医学影像 ：MRI(abstract,abstract_cn)；pathology(abstract)；diagnosis(abstract)；radiology(abstract)

AI总结 TumorBoard是基于证据的多智能体纵向神经肿瘤学决策支持系统，经360例基准测试，其性能优于现有基线，安全管控模块可有效降低有害建议比例。

MedSAM2-Anatomy: Training-Free Inference-Time Optimization for Musculoskeletal Segmentation

MedSAM2-Anatomy：面向肌肉骨骼分割的无训练推理时优化方法

John Garcia Henao, Nicholas Bünger, Benedikt Herzog, Cindy Guerrero Toro, Benjamin Vella, Matthias Biner, Rico Brütsch, Carmen Castroviejo Fernandez, Felix Öttl, Norman Juchler, Armando Hoch, Bettina Hochreiter, Sven Hirsch, Sebastiano Caprara

专题命中 医学影像 ：MRI(abstract,abstract_cn)；CT(abstract,abstract_cn)；分类 cs.CV、cs.LG、eess.IV

AI总结 MedSAM2-Anatomy是一种无训练的推理时优化框架，通过融合专家模型生成的自动解剖提示，提升冻结分割模型的髋部、肩部肌肉骨骼分割性能，无需人工提示或模型重训。

Comments Original research manuscript (13 pages, 4 figures, 2 tables). No prior publication

Tumor-anchored deep feature random forests for out-of-distribution detection in lung cancer segmentation

基于肿瘤锚定的深度特征随机森林用于肺癌分割中的分布外检测

Aneesh Rangnekar, Harini Veeraraghavan

机构 * Memorial Sloan Kettering Cancer Center（纪念斯隆凯特林癌症中心） 纠错

专题命中 医学影像 ：CT(summary_cn,abstract)；分类 cs.CV、cs.LG、eess.IV

AI总结 本文提出RF-Deep框架，利用深度特征提升CT扫描的分布外检测性能，通过少量标注数据改进分割管道的安全性。

Comments Accepted for publication in Transactions on Machine Learning Research (TMLR), 2026. Code available at: https://github.com/aneesh3108/RF-Deep

Longitudinal MRI template of the baboon brain from birth to adolescence

从出生到青春期的狒狒大脑纵向MRI模板

Katherine L. Bryant, Arnaud Le Troter, David Meunier, Yannick Becker, Scott A. Love, Siham Bouziane, Kep Kee Loh, Julien Sein, Luc Renaud, Olivier Coulon, Adrien Meguerditchian

专题命中 医学影像 ：MRI(title,title_cn)；分类 q-bio、eess.IV

AI总结 该研究针对狒狒大脑从出生到青春期的发育，提出BABACOOL方法创建多模态发育图谱，生成BaBa21纵向发育模板，还提供全自动生成中间年龄模板的方法，为狒狒数据归一化及相关研究提供便利。

Comments 21 pages, 6 Figures, 6 Supplementary Figures, In Press

Journal ref Imaging Neuroscience, 2026

Projection-Domain Sensitivity Analysis of Vertebral DRRs Under Intrinsic Calibration Perturbation

在固有校准扰动下椎体数字重建射线照片的投影域敏感性分析

Lin Li, Chaochao Zhou, Benjamin Aubert, Junlin Guo, Junchao Zhu

机构 * Department of Mathematics, Tulane University（特伦特大学数学系） ； Department of Computer Science, University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校计算机科学系） ； EOS, EOS Imaging Inc.（EOS公司） ； Department of Electrical and Computer Engineering, Vanderbilt University（范德比大学电气与计算机工程系） ； Department of Computer Science, Vanderbilt University（范德比大学计算机科学系） 纠错

专题命中 医学影像 ：CT(summary_cn,abstract)；分类 cs.CV、cs.LG、eess.IV

AI总结 研究固有校准扰动对椎体荧光透视投影及下游配准性能的影响，利用CT衍生模型等生成DRR，通过多种指标量化投影域变化，发现其受视图影响大，会降低配准精度，为评估校准鲁棒性提供框架以提高脊柱成像可靠性。