Test-time generative augmentation for medical image segmentation
测试时生成增强用于医学图像分割
Xiao Ma, Yuhui Tao, Zetian Zhang, Yuhan Zhang, Xi Wang, Sheng Zhang, Zexuan Ji, Yizhe Zhang, Qiang Chen, Guang Yang
机构
*
organization= School of Computer Science
；
Engineering, Nanjing University of Science
；
organization= Bioengineering Department
；
Imperial-X, Imperial College London , city= London , postcode= W12 7SL , country= UK
；
organization= Digital Medical Research Center, School of Basic Medical Sciences, Fudan University , city= Shanghai , country= China
；
organization= Shanghai Key Laboratory of MICCAI , city= Shanghai , country= China
；
organization= School of Biomedical Engineering, Shenzhen University , city= Shenzhen , country= China
；
organization= Department of Computer Science
；
Engineering, The Hong Kong University of Science
；
Engineering, The Chinese University of Hong Kong , city= Hong Kong , country= China
；
Lung Institute, Imperial College London , city= London , postcode= SW7 2AZ , country= UK
；
organization= Cardiovascular Research Centre, Royal Brompton Hospital , city= London , postcode= SW3 6NP , country= UK
；
organization= School of Biomedical Engineering \& Imaging Sciences, King's College London , city= London , postcode= WC2R 2LS , country= UK
MOIS-SAM2: Exemplar-based Segment Anything Model 2 for multilesion interactive segmentation of neurofibromas in whole-body MRI
MOIS-SAM2：基于示例的Segment Anything Model 2用于全身体部MRI中神经纤维瘤多病灶交互分割
Georgii Kolokolnikov, Marie-Lena Schmalhofer, Sophie Goetz, Lennart Well, Said Farschtschi, Victor-Felix Mautner, Inka Ristow, Rene Werner
机构
*
Institute for Applied Medical Informatics, Institute of Computational Neuroscience, and Center for Biomedical Artificial Intelligence (bAIome), University Medical Center Hamburg-Eppendorf（应用医学信息学研究所、计算神经科学研究所和生物医学人工智能中心（bAIome）、汉堡医学院中心）
；
Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf（诊断与介入放射学及核医学系、汉堡医学院中心）
；
Department of Neurology, University Medical Center Hamburg-Eppendorf（神经病学系、汉堡医学院中心）
AnyCXR: Human Anatomy Segmentation of Chest X-ray at Any Acquisition Position using Multi-stage Domain Randomized Synthetic Data with Imperfect Annotations and Conditional Joint Annotation Regularization Learning
机构
*
Department of Radiology, Northwestern University, Chicago, IL, USA（西北大学放射科）
；
Data Science Institute, Vanderbilt University, Nashville, TN, USA（范德比尔特大学数据科学研究院）
；
Department of Orthopedics, The Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, P.R. China（山西医科大学第二医院骨科）
；
Second Clinical Medical College, Shanxi Medical University, Taiyuan, Shanxi, P.R. China（山西医科大学第二临床医学院）
；
School of Computer Science, University of Sydney, Sydney, NSW, Australia（悉尼大学计算机科学学院）
