医学 AI

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。

False Confidence: Automated Labels Confound Fairness Audits in Cervical Spine Segmentation

错误置信度：颈椎分割中的自动标签混淆公平性审计

Linus Juni, Aasa Feragen, Aditya Parikh

机构 * Section for Visual Computing, DTU Compute, Technical University of Denmark（视觉计算部门，丹麦技术大学） 纠错

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

AI总结 研究针对颈椎MRI分割无公平性审计的问题，利用CSpineSeg数据集进行审计，发现参考标签选择非中立，银标签会使模型性能高估、公平性判定改变，指出参考标签来源是分割评估的混杂因素，应依专家标签报告性能与公平性并说明参考来源。

Comments 8 pages, 1 figure. Under review at FAIMI 2026 (MICCAI workshop)

Complete virtual unwrapping and reading of a rolled Herculaneum papyrus

完整虚拟展开与阅读一卷卷起的赫库兰尼姆纸莎草

Giorgio Angelotti, Stephen Parsons, Federica Nicolardi, Youssef Nader, Sean Johnson, David Josey, Paul Henderson, Hendrik Schilling, Johannes Rudolph, Forrest McDonald, Elian Rafael Dal Prá, Paul Tafforeau, Alessandro Mirone, Clifford Seth Parker, Jan Paul Posma, Benjamin Kyles, Claudio Vergara, Alessia Lavorante, Rossella Villa, Maria Chiara Robustelli, Marzia D'Angelo, Gianluca Del Mastro, Michael McOsker, Kilian Fleischer, Christy Chapman, Nat Friedman, William Brent Seales

机构 * Vesuvius Challenge, San Francisco, CA, USA（维苏威挑战，美国加州旧金山） ； EduceLab, University of Kentucky, Lexington, KY, USA（EduceLab，肯塔基大学，美国肯塔基州列克星敦） ； Università degli Studi di Napoli Federico II, Napoli, Italy（那不勒斯费德里科二世大学，意大利那不勒斯） ； University of Glasgow, Glasgow, UK（格拉斯哥大学，英国格拉斯哥） ； ESRF, Grenoble, France（欧洲同步辐射研究中心，法国格勒诺布尔） ； Università di Salerno, Salerno, Italy（萨勒诺大学，意大利萨勒诺） ； Università degli Studi della Campania Luigi Vanvitelli, S. Maria Capua Vetere, Italy（坎帕尼亚卢吉·范维蒂利大学，意大利圣玛丽亚·卡普阿·韦特里） ； University College London, London, UK（伦敦大学学院，英国伦敦） ； Universität Tübingen, Tübingen, Germany（图宾根大学，德国图宾根） 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 利用高分辨率相衬显微CT和改进的机器学习方法，首次完整虚拟展开并阅读了赫库兰尼姆纸莎草卷PHerc. 1667，无需物理打开，并验证了墨迹恢复方法，为系统恢复未打开卷轴提供了可扩展框架。

Comments Preprint, 4 main figures

An Empirical Study on Variance-based MC Dropout Uncertainty-Error Correlation in 2D Brain Tumor Segmentation

基于方差的MC Dropout不确定性-误差相关性在二维脑肿瘤分割中的实证研究

Saumya B

机构 * Project Associate DESE, Indian Institute of Science（DESE项目助理，印度科学研究院） 纠错

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

AI总结 通过U-Net在四种增强设置下的实验，发现基于方差的MC Dropout不确定性在全局和边界上与分割误差的相关性较弱，表明其局限性。

Comments v2: Updated title and framing to clarify that findings are specific to variance-based uncertainty estimation via MC Dropout, not MC Dropout broadly. Minor textual improvements throughout. Code and results available at https://github.com/Saumya4321/mcd-error-correlation

Learning spatially adaptive sparsity level maps for arbitrary convolutional dictionaries

学习任意卷积字典的时空自适应稀疏性水平图

Joshua Schulz, David Schote, Christoph Kolbitsch, Kostas Papafitsoros, Andreas Kofler

机构 * Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany（物理技术联邦机构（PTB），柏林和不莱梅，德国） ； School of Mathematical Sciences, Queen Mary University of London, UK（伦敦女王学院数学科学学院，英国） 纠错

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

AI总结 本文提出了一种学习方法，通过改进的网络设计和专门的训练策略，扩展了基于神经网络推断的时空自适应稀疏性水平图的图像重建方法，实现了滤波器排列不变性，并在低场MRI中展示了使用不同字典的优势。

Comments accepted for publication at ICIP 2026; differs from previous versions after a bugfix in one of the used packages; corresponds to the final camera-ready version submitted to the conference

SlicerRoboTMS: An Open-Source 3D Slicer Extension for Robot-Assisted Transcranial Magnetic Stimulation

SlicerRoboTMS：一种用于机器人辅助经颅磁刺激的开源3D切片扩展

Wenzhi Bai, Yituo Guo, Bhaskar Basu, Andrew Weightman, Zhenhong Li

机构 * Department of Electrical and Electronic Engineering（电气与电子工程系） ； University of Manchester（曼彻斯特大学） ； Rehabilitation Medicine（康复医学） ； Manchester University NHS Foundation Trust（曼彻斯特大学国家健康服务基金会信托） ； Department of Mechanical and Aerospace Engineering（机械与航空航天工程系） 纠错

专题命中 医学影像 ：MRI(summary_cn,abstract)；medical image(abstract)

AI总结 本文提出SlicerRoboTMS，一种开源3D切片扩展，通过统一交互基础设施支持机器人辅助经颅磁刺激研究，提供MRI导航和机器人系统接口，降低研究门槛，促进可重复和扩展的研究。

Comments Accepted by the 48th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2026

Behavior Score Prediction in Resting-State Functional MRI by Deep State Space Modeling

通过深度状态空间建模预测静息态功能磁共振成像中的行为评分

Javier Salazar Cavazos, Maximillian Egan, Krisanne Litinas, Benjamin Hampstead, Scott Peltier

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

AI总结 本文提出深度状态空间模型，利用血氧水平依赖时间序列预测行为评分，通过实验发现特定脑区与认知损伤相关，为阿尔茨海默病早期病理研究提供新见解。

Privacy-Preserving Collaborative Medical Image Segmentation Using Latent Transform Networks

基于潜在变换网络的隐私保护协作医学图像分割

Saheed Ademola Bello, Muhammad Shahid Jabbar, Muhammad Sohail Ibrahim, Shujaat Khan

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

AI总结 本文提出PPCMI-SF框架，通过潜在变换网络实现隐私保护的医学图像分割，提升分割精度并抵御潜在攻击。

Comments 14 pages, 8 figures

Free Lunch in Medical Image Foundation Model Pre-training via Randomized Synthesis and Disentanglement

通过随机合成与解构在医疗图像基础模型预训练中获得免费午餐

Yuhan Wei, Yuting He, Linshan Wu, Fuxiang Huang, Junlin Hou, Hao Chen

机构 * Department of Computer Science and Engineering, the Hong Kong University of Science and Technology, Hong Kong, China（香港科技大学计算机科学与工程系） ； Department of Biomedical Engineering, Case Western Reserve University, OH, USA（凯斯西储大学生物医学工程系） ； School of Data Science, Lingnan University, Hong Kong, China（岭南大学数据科学学院） ； Department of Chemical and Biological Engineering and Division of Life Science, Hong Kong University of Science and Technology, Hong Kong, China（香港科技大学化学与生物工程系） ； HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute, Futian, Shenzhen, China（香港科技大学深圳-香港协同创新研究院） ； State Key Laboratory of Nervous System Disorders, The Hong Kong University of Science and Technology, Hong Kong, China（香港科技大学神经系统疾病国家重点实验室） 纠错

专题命中 医学影像 ：medical image(title,abstract)；medical AI(abstract)；分类 cs.LG、q-bio

AI总结 本文提出RaSD框架，通过随机合成与解构方法在无需真实数据的情况下预训练医疗图像基础模型，实现稳健且可迁移的表示学习，展示了合成数据在医学AI中的强大潜力。

Data Exfiltration by Compression Attack: Definition and Evaluation on Medical Image Data

通过压缩攻击的数据外泄：在医学图像数据中的定义与评估

Huiyu Li, Nicholas Ayache, Hervé Delingette

专题命中 医学影像 ：medical image(title,abstract)；CT(abstract)；biomedical(comments,journal_ref)

AI总结 本文提出了一种基于图像压缩的新型数据外泄攻击，通过医学图像数据验证其有效性，并探讨了差分隐私等防护措施的应对策略。

Comments Accepted for publication at the Journal of Machine Learning for Biomedical Imaging (MELBA) https://melba-journal.org/2025:032

Journal ref Machine.Learning.for.Biomedical.Imaging. 3 (2025)

Analysis of the MICCAI Brain Tumor Segmentation -- Metastases (BraTS-METS) 2025 Lighthouse Challenge: Brain Metastasis Segmentation on Pre- and Post-treatment MRI

Nazanin Maleki, Raisa Amiruddin, Ahmed W. Moawad, Nikolay Yordanov, Athanasios Gkampenis, Pascal Fehringer, Fabian Umeh, Crystal Chukwurah, Fatima Memon, Bojan Petrovic, Justin Cramer, Mark Krycia, Elizabeth B. Shrickel, Ichiro Ikuta, Gerard Thompson, Lorenna Vidal, Vilma Kosovic, Adam E. Goldman-Yassen, Virginia Hill, Tiffany So, Sedra Mhana, Albara Alotaibi, Nathan Page, Prisha Bhatia, Melisa S. Guelen, Yasaman Sharifi, Marko Jakovljevic, Salma Abosabie, Sara Abosabie, Mohanad Ghonim, Mohamed Ghonim, Amirreza Manteghinejad, Anastasia Janas, Kiril Krantchev, Maruf Adewole, Jake Albrecht, Udunna Anazodo, Sanjay Aneja, Syed Muhammad Anwar, Timothy Bergquist, Veronica Chiang, Verena Chung, Gian Marco Conte, Farouk Dako, James Eddy, Ivan Ezhov, Nastaran Khalili, Keyvan Farahani, Juan Eugenio Iglesias, Zhifan Jiang, Elaine Johanson, Anahita Fathi Kazerooni, Florian Kofler, Dominic LaBella, Koen Van Leemput, Hongwei Bran Li, Marius George Linguraru, Xinyang Liu, Zeke Meier, Bjoern H Menze, Harrison Moy, Klara Osenberg, Marie Piraud, Zachary Reitman, Russell Takeshi Shinohara, Chunhao Wang, Benedikt Wiestler, Walter Wiggins, Umber Shafique, Klara Willms, Arman Avesta, Khaled Bousabarah, Satrajit Chakrabarty, Nicolo Gennaro, Wolfgang Holler, Manpreet Kaur, Pamela LaMontagne, MingDe Lin, Jan Lost, Daniel S. Marcus, Ryan Maresca, Sarah Merkaj, Gabriel Cassinelli Pedersen, Marc von Reppert, Aristeidis Sotiras, Oleg Teytelboym, Niklas Tillmans, Malte Westerhoff, Ayda Youssef, Devon Godfrey, Scott Floyd, Andreas Rauschecker, Javier Villanueva-Meyer, Irada Pflüger, Jaeyoung Cho, Martin Bendszus, Gianluca Brugnara, Gloria J. Guzman Perez-Carillo, Derek R. Johnson, Anthony Kam, Benjamin Yin Ming Kwan, Lillian Lai, Neil U. Lall, Satya Narayana Patro, Lei Wu, Anu Bansal, Frederik Barkhof, Cristina Besada, Sammy Chu, Jason Druzgal, Alexandru Dusoi, Luciano Farage, Fabricio Feltrin, Amy Fong, Steve H. Fung, R. Ian Gray, Michael Iv, Alida A. Postma, Amit Mahajan, David Joyner, Chase Krumpelman, Laurent Letourneau-Guillon, Christie M. Lincoln, Mate E. Maros, Elka Miller, Fanny Morón, Esther A. Nimchinsky, Ozkan Ozsarlak, Uresh Patel, Saurabh Rohatgi, Atin Saha, Anousheh Sayah, Eric D. Schwartz, Robert Shih, Mark S. Shiroishi, Juan E. Small, Manoj Tanwar, Jewels Valerie, Brent D. Weinberg, Matthew L. White, Robert Young, Vahe M. Zohrabian, Aynur Azizova, Melanie Maria Theresa Brüßeler, Abdullah Okar, Luca Pasquini, Yasaman Sharifi, Gagandeep Singh, Nico Sollmann, Theodora Soumala, Mahsa Taherzadeh, Philipp Vollmuth, Martha Foltyn-Dumitru, Ajay Malhotra, Francesco Dellepiane, Víctor M. Pérez-García, Hesham Elhalawani, Maria Correia de Verdier, Sanaria Al Rubaiey, Rui Duarte Armindo, Kholod Ashraf, Moamen M. Asla, Mohamed Badawy, Jeroen Bisschop, Nima Broomand Lomer, Jan Bukatz, Jim Chen, Petra Cimflova, Felix Corr, Alexis Crawley, Lisa Deptula, Tasneem Elakhdar, Islam H. Shawali, Shahriar Faghani, Alexandra Frick, Vaibhav Gulati, Muhammad Ammar Haider, Fátima Hierro, Rasmus Holmboe Dahl, Sarah Maria Jacobs, Kuang-chun Jim Hsieh, Sedat G. Kandemirli, Katharina Kersting, Laura Kida, Sofia Kollia, Ioannis Koukoulithras, Xiao Li, Ahmed Abouelatta, Aya Mansour, Ruxandra-Catrinel Maria-Zamfirescu, Marcela Marsiglia, Yohana Sarahi Mateo-Camacho, Mark McArthur, Olivia McDonnel, Maire McHugh, Mana Moassefi, Samah Mostafa Morsi, Alexander Munteanu, Khanak K. Nandolia, Syed Raza Naqvi, Yalda Nikanpour, Mostafa Alnoury, Abdullah Mohamed Aly Nouh, Francesca Pappafava, Markand D. Patel, Samantha Petrucci, Eric Rawie, Scott Raymond, Borna Roohani, Sadeq Sabouhi, Laura M. Sanchez Garcia, Zoe Shaked, Pokhraj P. Suthar, Talissa Altes, Edvin Isufi, Yaseen Dhemesh, Jaime Gass, Jonathan Thacker, Abdul Rahman Tarabishy, Benjamin Turner, Sebastiano Vacca, George K. Vilanilam, Daniel Warren, David Weiss, Fikadu Worede, Sara Yousry, Wondwossen Lerebo, Alejandro Aristizabal, Alexandros Karargyris, Hasan Kassem, Sarthak Pati, Micah Sheller, Katherine E. Link, Evan Calabrese, Nourel Hoda Tahon, Ayman Nada, Jeffrey D. Rudie, Janet Reid, Kassa Darge, Aly H. Abayazeed, Philipp Lohmann, Yuri S. Velichko, Spyridon Bakas, Mariam Aboian

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

Comments 28 pages, 4 figures, 2 tables

CryptoUNets: Applying Convolutional Networks to Encrypted Data for Biomedical Image Segmentation

John Chiang

专题命中 医学影像 ：medical image(title)；biomedical(title)

Single-shot Star-convex Polygon-based Instance Segmentation for Spatially-correlated Biomedical Objects

Trina De, Adrian Urbanski, Artur Yakimovich

专题命中 医学影像 ：biomedical(title,abstract)；medical image(abstract)；分类 cs.CV、q-bio

Comments 12 pages, 8 figures

Opportunistic Screening for Pancreatic Cancer using Computed Tomography Imaging and Radiology Reports

David Le, Ramon Correa-Medero, Amara Tariq, Bhavik Patel, Motoyo Yano, Imon Banerjee

专题命中 医学影像 ：radiology(title,abstract)；CT(abstract)；分类 cs.LG、q-bio

Comments 8 pages, 2 figures, AMIA 2025 Annual Symposium

Conditional Generative Models for Contrast-Enhanced Synthesis of T1w and T1 Maps in Brain MRI

Moritz Piening, Fabian Altekrüger, Gabriele Steidl, Elke Hattingen, Eike Steidl

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

GAN-GA: A Generative Model based on Genetic Algorithm for Medical Image Generation

M. AbdulRazek, G. Khoriba, M. Belal

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

Comments 10 pages, 2 figures. Abstract published in Frontiers in Medical Technology, presented at the 27th Conference on Medical Image Understanding and Analysis 2023. DOI: 10.3389/978-2-8325-1231-9. URL: https://doi.org/10.3389/978-2-8325-1231-9

Journal ref 27th Conference on Medical Image Understanding and Analysis 2023, Frontiers, 2023, pp. 30-39