医学 AI

Improving Uncertainty-Error Correspondence in Deep Bayesian Medical Image Segmentation

Prerak Mody, Nicolas F. Chaves-de-Plaza, Chinmay Rao, Eleftheria Astrenidou, Mischa de Ridder, Nienke Hoekstra, Klaus Hildebrandt, Marius Staring

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

Comments Accepted for publication at the Journal of Machine Learning for Biomedical Imaging (MELBA) https://melba-journal.org/2024:018

Journal ref Machine.Learning.for.Biomedical.Imaging. 2 (2024)

Bayesian Uncertainty Estimation by Hamiltonian Monte Carlo: Applications to Cardiac MRI Segmentation

Yidong Zhao, Joao Tourais, Iain Pierce, Christian Nitsche, Thomas A. Treibel, Sebastian Weingärtner, Artur M. Schweidtmann, Qian Tao

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

Comments Accepted for publication at the Journal of Machine Learning for Biomedical Imaging (MELBA) https://melba-journal.org/2024:011

Journal ref Machine.Learning.for.Biomedical.Imaging. 2 (2024)

Synthesizing Missing MRI Sequences from Available Modalities using Generative Adversarial Networks in BraTS Dataset

Ibrahim Ethem Hamamci

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

Comments Wrong paper submission

Efficiently Training Vision Transformers on Structural MRI Scans for Alzheimer's Disease Detection

Nikhil J. Dhinagar, Sophia I. Thomopoulos, Emily Laltoo, Paul M. Thompson

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

Freehand 2D Ultrasound Probe Calibration for Image Fusion with 3D MRI/CT

Yogesh Langhe, Katrin Skerl, Adrien Bartoli

专题命中 医学影像 ：MRI(title)；CT(title)；分类 cs.CV、eess.IV

An Interpretable MRI Reconstruction Network with Two-grid-cycle Correction and Geometric Prior Distillation

Xiaohong Fan, Yin Yang, Ke Chen, Jianping Zhang, Ke Dong

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

Comments 14 pages, accepted to Biomedical Signal Processing and Control,March, 2023

Journal ref Biomedical Signal Processing and Control, vol 84, 2023

Rethinking Generalization: The Impact of Annotation Style on Medical Image Segmentation

Brennan Nichyporuk, Jillian Cardinell, Justin Szeto, Raghav Mehta, Jean-Pierre R. Falet, Douglas L. Arnold, Sotirios A. Tsaftaris, Tal Arbel

专题命中 医学影像 ：medical image(title,abstract)；clinical AI(abstract)；biomedical(comments,journal_ref)；分类 cs.CV、eess.IV

Comments Accepted for publication at the Journal of Machine Learning for Biomedical Imaging (MELBA) https://www.melba-journal.org/papers/2022:029.html

Journal ref Machine.Learning.for.Biomedical.Imaging. 1 (2022)

Learning Generalized Non-Rigid Multimodal Biomedical Image Registration from Generic Point Set Data

Zachary MC Baum, Tamas Ungi, Christopher Schlenger, Yipeng Hu, Dean C Barratt

专题命中 医学影像 ：medical image(title)；biomedical(title)；分类 cs.CV、cs.LG

Comments Accepted to ASMUS 2022 Workshop at MICCAI

Improving Disease Classification Performance and Explainability of Deep Learning Models in Radiology with Heatmap Generators

Akino Watanabe, Sara Ketabi, Khashayar, Namdar, Farzad Khalvati

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

SODA: Self-organizing data augmentation in deep neural networks -- Application to biomedical image segmentation tasks

Arnaud Deleruyelle, John Klein, Cristian Versari

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

MRI Images, Brain Lesions and Deep Learning

Darwin Castillo, Vasudevan Lakshminarayanan, Maria J. Rodriguez-Alvarez

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

Comments Submitted to: Computer Programs and Methods in Biomedicine update (2021)

A Transfer Learning Approach for Automated Segmentation of Prostate Whole Gland and Transition Zone in Diffusion Weighted MRI

Saman Motamed, Isha Gujrathi, Dominik Deniffel, Anton Oentoro, Masoom A. Haider, Farzad Khalvati

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

Interpretation of 3D CNNs for Brain MRI Data Classification

Maxim Kan, Ruslan Aliev, Anna Rudenko, Nikita Drobyshev, Nikita Petrashen, Ekaterina Kondrateva, Maxim Sharaev, Alexander Bernstein, Evgeny Burnaev

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

Comments 12 pages, 3 figures

Journal ref AIST2020

3D Deep Learning on Medical Images: A Review

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

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

Comments Published in Sensors Journal (https://www.mdpi.com/1424-8220/20/18/5097)

Journal ref Sensors 2020, 20, 5097

Region Growing with Convolutional Neural Networks for Biomedical Image Segmentation

John Lagergren, Erica Rutter, Kevin Flores

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

The reliability of a deep learning model in clinical out-of-distribution MRI data: a multicohort study

Gustav Mårtensson, Daniel Ferreira, Tobias Granberg, Lena Cavallin, Ketil Oppedal, Alessandro Padovani, Irena Rektorova, Laura Bonanni, Matteo Pardini, Milica Kramberger, John-Paul Taylor, Jakub Hort, Jón Snædal, Jaime Kulisevsky, Frederic Blanc, Angelo Antonini, Patrizia Mecocci, Bruno Vellas, Magda Tsolaki, Iwona Kłoszewska, Hilkka Soininen, Simon Lovestone, Andrew Simmons, Dag Aarsland, Eric Westman

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

Comments 11 pages, 3 figures

DRU-net: An Efficient Deep Convolutional Neural Network for Medical Image Segmentation

Mina Jafari, Dorothee Auer, Susan Francis, Jonathan Garibaldi, Xin Chen

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

Comments Accepted for publication at IEEE International Symposium on Biomedical Imaging (ISBI) 2020, 5 pages, 3 figures

Journal ref 2020 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2020)

AI-Driven CT-based quantification, staging and short-term outcome prediction of COVID-19 pneumonia

Guillaume Chassagnon, Maria Vakalopoulou, Enzo Battistella, Stergios Christodoulidis, Trieu-Nghi Hoang-Thi, Severine Dangeard, Eric Deutsch, Fabrice Andre, Enora Guillo, Nara Halm, Stefany El Hajj, Florian Bompard, Sophie Neveu, Chahinez Hani, Ines Saab, Alienor Campredon, Hasmik Koulakian, Souhail Bennani, Gael Freche, Aurelien Lombard, Laure Fournier, Hippolyte Monnier, Teodor Grand, Jules Gregory, Antoine Khalil, Elyas Mahdjoub, Pierre-Yves Brillet, Stephane Tran Ba, Valerie Bousson, Marie-Pierre Revel, Nikos Paragios

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

Residual Attention U-Net for Automated Multi-Class Segmentation of COVID-19 Chest CT Images

Xiaocong Chen, Lina Yao, Yu Zhang

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

Accuracy of MRI Classification Algorithms in a Tertiary Memory Center Clinical Routine Cohort

Alexandre Morin, Jorge Samper-González, Anne Bertrand, Sebastian Stroer, Didier Dormont, Aline Mendes, Pierrick Coupé, Jamila Ahdidan, Marcel Lévy, Dalila Samri, Harald Hampel, Bruno Dubois, Marc Teichmann, Stéphane Epelbaum, Olivier Colliot

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

Journal ref Journal of Alzheimer's Disease, IOS Press, 2020, pp.1-10

Distribution Matching Losses Can Hallucinate Features in Medical Image Translation

Joseph Paul Cohen, Margaux Luck, Sina Honari

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

Comments Published at Medical Image Computing & Computer Assisted Intervention (MICCAI 2018). An abstract is published at the Medical Imaging with Deep Learning Conference (MIDL 2018) as "How to Cure Cancer (in images) with Unpaired Image Translation"

Journal ref Medical Image Computing & Computer Assisted Intervention (MICCAI 2018 Oral)

Segmentation Pre-training for Label-Efficient Lumbar Spine Degeneration Grading

用于标签高效腰椎退变分级的分割预训练

Monzon Maria, Zisserman Andrew, Jutzeler Catherine R., Jamaludin Amir

机构 * ETH Zurich（苏黎世联邦理工学院） ； Swiss Institute of Bioinformatics (SIB)（瑞士生物信息学研究所） ； University of Oxford（牛津大学） 纠错

专题命中 医学影像 ：MRI(summary_cn,abstract)；pathology(abstract)；分类 cs.CV；medical AI(comments)

AI总结 本研究探究用分割预训练替代部分手动分级标注，在约2000名受试者的多中心腰椎MRI数据集上，该方法仅用20%分级标签即可接近全监督性能，提升了腰椎退变分级效果。

Comments The 2nd MICCAI Workshop on Efficient Medical AI (2026)

DrivenMorph: Bridging Attention Mechanism and Variational Image Registration via Difference Modeling

DrivenMorph: 通过差异建模桥接注意力机制与变分图像配准

Mingke Li, Jianping Zhang, Jinqiu Deng

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

AI总结 提出DrivenMorph框架，通过差异建模作为物理启发归纳偏置，结合注意力机制与变分图像配准，利用神经Demons层模拟力-位移交互生成平滑形变，在3D脑MRI数据集上优于现有方法。

Comments 14 pages

Journal ref IEEE Journal of Biomedical and Health Informatics, 2026

Pre-examinations Improve Automated Metastases Detection on Cranial MRI

Katerina Deike-Hofmann, Dorottya Dancs, Daniel Paech, Heinz-Peter Schlemmer, Klaus Maier-Hein, Philipp Bäumer, Alexander Radbruch, Michael Götz

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

Journal ref Investigative Radiology 56(5):p 320-327, May 2021

Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review

Parisa Moridian, Navid Ghassemi, Mahboobeh Jafari, Salam Salloum-Asfar, Delaram Sadeghi, Marjane Khodatars, Afshin Shoeibi, Abbas Khosravi, Sai Ho Ling, Abdulhamit Subasi, Roohallah Alizadehsani, Juan M. Gorriz, Sara A Abdulla, U. Rajendra Acharya

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

Journal ref Moridian, et. al., Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review, Frontiers in Molecular Neuroscience, Volume 15, 2022

Multi-Agent AI System for Radiology Report Structuring and Quality Assurance with Independent Radiologist Evaluation

用于放射科报告结构化与质量保证的多智能体AI系统：独立放射科医师评估

Iryna Hartsock, Cesar Lam, Christopher Otteni, Aliya Qayyum, Robert Gatenby, Cyrillo Araujo, Ghulam Rasool

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

AI总结 本研究开发了一款本地部署的多智能体AI系统，可实现放射科报告结构化与质量保证，经独立放射科医师评估，该系统表现良好，或有助于放射科报告标准化。

Comments 14 pages, 2 figures, 4 tables

Evidence-Linked Radiology Reporting: A Human-Supervised Reference Architecture for Structured Imaging Intelligence

证据关联放射学报告：面向结构化成像智能的人机协同参考架构

Houman Kazemzadeh, Kamyar Naderi

机构 * Xylemed 纠错

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

AI总结 提出一种人机协同、证据关联的参考架构，通过结合特定检查模板、语音到结构处理、测量与分割捕获、受控AI辅助起草以及基于DICOM、HL7 FHIR等标准的互操作性，将放射学报告从自由文本转化为结构化智能层，支持审阅报告、纵向比较、临床数据重用及系统集成。

Comments Technical report, 27 pages, 2 figures, 12 tables, 1 listing; reference architecture paper; does not report clinical outcomes or validated diagnostic performance

Homology-based Morphometry of Brain Atrophy: Methods and Applications

基于同调的脑萎缩形态学：方法与应用

Donato Quiccione, Mariam Pirashvili, Nathan Broomhead, Sean J. Fallon

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

AI总结 本文提出基于持续同调的两种方法，用于量化脑结构T1加权MRI的多尺度几何特征，通过合成实验验证其在跨受试者和跨时间分析中的有效性，并应用于ADNI数据展示其在脑萎缩检测与纵向跟踪中的应用。

Delving Aleatoric Uncertainty in Medical Image Segmentation via Vision Foundation Models

深入探讨医学图像分割中的随机不确定性：通过视觉基础模型

Ruiyang Li, Fang Liu, Licheng Jiao, Xinglin Xie, Jiayao Hao, Shuo Li, Xu Liu, Jingyi Yang, Lingling Li, Puhua Chen, Wenping Ma

机构 * Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education（教育部智能感知与图像理解重点实验室） ； International Research Center for Intelligent Perception and Computation（智能感知与计算国际研究中心） ； Joint International Research Laboratory of Intelligent Perception and Computation（智能感知与计算联合国际研究实验室） ； School of Artificial Intelligence, Xidian University（西安电子科技大学人工智能学院） 纠错

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

AI总结 本文通过视觉基础模型分析医学图像分割中的数据不确定性，提出数据过滤和动态优化策略，提升模型鲁棒性和分割性能。

Subclass Classification of Gliomas Using MRI Fusion Technique

使用MRI融合技术对胶质瘤进行亚类分类

Kiranmayee Janardhan, Christy Bobby Thomas

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

AI总结 本研究提出一种基于MRI融合技术的胶质瘤亚类分类方法，通过融合多模态MRI图像提升分类精度，达到99.25%的准确率。

Comments 15 pages, 7 figures, 1 algorithm, 4 tables, journal paper

Journal ref SN Computer Science, 2025