Image Segmentation plays an essential role in computer vision and image processing with various applications from medical diagnosis to autonomous car driving. A lot of segmentation algorithms have been proposed for addressing specific problems. In recent years, the success of deep learning techniques has tremendously influenced a wide range of computer vision areas, and the modern approaches of image segmentation based on deep learning are becoming prevalent. In this article, we introduce a high-efficient development toolkit for image segmentation, named PaddleSeg. The toolkit aims to help both developers and researchers in the whole process of designing segmentation models, training models, optimizing performance and inference speed, and deploying models. Currently, PaddleSeg supports around 20 popular segmentation models and more than 50 pre-trained models from real-time and high-accuracy levels. With modular components and backbone networks, users can easily build over one hundred models for different requirements. Furthermore, we provide comprehensive benchmarks and evaluations to show that these segmentation algorithms trained on our toolkit have more competitive accuracy. Also, we provide various real industrial applications and practical cases based on PaddleSeg. All codes and examples of PaddleSeg are available at https://github.com/PaddlePaddle/PaddleSeg.
What a MESS: Multi-Domain Evaluation of Zero-Shot Semantic Segmentation
Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院）；IBM Research Europe（IBM欧洲研究院）；University of Bonn（波恩大学）；MIT-IBM Watson AI Lab（麻省理工学院-IBM沃森人工智能实验室）；IBM Germany（IBM德国公司）
PyMIC: A deep learning toolkit for annotation-efficient medical image segmentation
University of Electronic Science and Technology of China（电子科技大学）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；Johns Hopkins University（约翰斯·霍普金斯大学）；West China Hospital, Sichuan University（四川大学华西医院）
SynVA: A Modular Toolkit for Vessel Generation and Aneurysm Editing
Visual Computing and Artificial Intelligence, Kiel University, Germany（视觉计算与人工智能研究所，基尔大学，德国）；Institute for Medical Informatics and Statistics, Kiel University, Germany（医学信息学与统计研究所，基尔大学，德国）；Clinic for Neuroradiology, Medical Faculty, Magdeburg University, Germany（神经放射科，马格德堡大学医学学院，德国）；Department of Radiology and Neuroradiology, University Hospital Schleswig-Holstein, Germany（放射学与神经放射学部门，石勒苏益格-荷尔斯泰因大学医院，德国）；Faculty of Mathematics and Computer Science, Adam Mickiewicz University, Poland（数学与计算机科学学院，亚当·密茨凯维奇大学，波兰）
CataractSAM-2: A Domain-Adapted Model for Anterior Segment Surgery Segmentation and Scalable Ground-Truth Annotation
Thomas Jefferson High School for Science and Technology（托马斯·杰弗逊高中科学与技术学校）；Mass Eye and Ear, Harvard Medical School（麻省眼耳研究所，哈佛医学院）；Harvard Ophthalmology AI Lab, Schepens Eye Research Institute of Mass Eye and Ear, Harvard Medical School（哈佛眼科学人工智能实验室，麻省眼耳研究所的谢普恩斯眼研究学院，哈佛医学院）
A Unified Framework for Foreground and Anonymization Area Segmentation in CT and MRI Data
German Cancer Research Center (DKFZ)（德国癌症研究中心）；Brno University of Technology（布尔诺理工大学）；University hospital Ostrava（俄斯特拉发大学医院）；Heidelberg University Hospital（海德堡大学医院）；National Center for Tumor Diseases (NCT)（国家肿瘤疾病中心）；University of Heidelberg（海德堡大学）；Heidelberg University（海德堡大学）
SLOctolyzer: Fully automatic analysis toolkit for segmentation and feature extracting in scanning laser ophthalmoscopy images
University of Edinburgh（爱丁堡大学）；Institute for Regeneration and Repair, University of Edinburgh（爱丁堡大学再生与修复研究所）；Centre for Medical Informatics, University of Edinburgh（爱丁堡大学医学信息学中心）；School of Informatics, University of Edinburgh（爱丁堡大学信息学院）；Clinical Research Facility and Imaging, University of Edinburgh（爱丁堡大学临床研究设施与影像中心）；School of Mathematics, University of Edinburgh（爱丁堡大学数学学院）；Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh（爱丁堡大学信息学院自适应与神经计算研究所）；Centre for Clinical Brain Sciences, University of Edinburgh（爱丁堡大学临床脑科学中心）
OCTolyzer: Fully automatic toolkit for segmentation and feature extracting in optical coherence tomography and scanning laser ophthalmoscopy data
University of Edinburgh（爱丁堡大学）；Institute for Regeneration and Repair（再生与修复研究所）；Glasgow Caledonian University（格拉斯哥卡利多尼亚大学）；British Heart Foundation Centre for Cardiovascular Science（英国心脏基金会心血管科学中心）；Clinical Research Facility and Imaging（临床研究设施与影像中心）；Centre for Clinical Brain Sciences（临床脑科学中心）；School of Informatics（信息学院）；Institute for Adaptive and Neural Computation（自适应与神经计算研究所）；School of Mathematics（数学学院）
Keep It Accurate and Robust: An Enhanced Nuclei Analysis Framework
Institute of Artificial Intelligence, Shanghai University（上海大学人工智能研究院）；Stanford University School of Medicine（斯坦福大学医学院）；Tencent AI Lab（腾讯AI实验室）；Shanghai Aitrox Technology Corporation Limited（上海艾特瑞克斯科技有限公司）；The Affiliated Yantai Yuhuangding Hospital of Qingdao University（青岛大学附属烟台毓璜顶医院）
Efficient Large Scale Medical Image Dataset Preparation for Machine Learning Applications
German Cancer Research Center (DKFZ)（德国癌症研究中心（DKFZ））；University of Heidelberg（海德堡大学）；Goethe University Frankfurt（法兰克福歌德大学）；Charité - Universitätsmedizin Berlin（柏林夏里特医学院）
A tissue and cell-level annotated H&E and PD-L1 histopathology image dataset in non-small cell lung cancer
Radboud University Medical Center（拉德堡德大学医学中心）；University of Brescia（布雷西亚大学）；Ospedale Sacro Cuore（圣十字医院）；Provincial Hospital of Bolzano (SABES-ASDAA)（博尔扎诺省医院）；University and Hospital Trust of Verona（威尼斯大学与医院信托）；Karolinska University Hospital（卡罗林斯卡大学医院）；Biopticka Laboratory, Ltd（Biopticka实验室）
BrainLesion Suite: A Flexible and User-Friendly Framework for Modular Brain Lesion Image Analysis
Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland（苏黎世大学定量生物医学系）；Helmholtz AI, Helmholtz Zentrum München, Germany（海德堡人工智能，慕尼黑研究中心）；Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Germany（医学诊断与介入神经放射学系，慕尼黑技术大学）；TranslaTUM - Central Institute for Translational Cancer Research, Technical University of Munich, Germany（TranslaTUM - 转化癌症研究中央研究所，慕尼黑技术大学）；Chair for AI in Medicine, Klinikum Rechts der Isar, Munich, Germany（医学人工智能系，慕尼黑Klinikum Rechts der Isar）；Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Germany（放射肿瘤学系，慕尼黑Klinikum Rechts der Isar）；Institute of Clinical Neuroimmunology, Faculty of Medicine, Ludwig Maximilian University, Munich, Germany（临床神经免疫学研究所，路德维希-马克西米利安大学）；School of Computation, Information and Technology, Technical University of Munich, Germany（计算、信息与技术学院，慕尼黑技术大学）；Division of Computational Pathology, Indiana School of Medicine, Indianapolis, IN, USA（计算病理学系，印第安纳医学院）；Research Center for Digital Technologies in Dentistry and CAD/CAM, Department of Dentistry, Faculty of Medicine and Dentistry, Danube Private University, Krems, Austria（牙科数字技术研究中心，医学与牙科学院，多瑙私人大学）；Medical Research Group, MLCommons, San Francisco, CA, USA（医学研究组，MLCommons，旧金山，美国）；Department of Neurology, Clinical Neuroscience Center and Brain Tumor Center, University and University Hospital Zurich, 8091 Zurich, Switzerland（神经学系，临床神经科学中心和脑肿瘤中心，苏黎世大学及苏黎世大学医院）；Department of Medical Radiation Physics, Stockholm University, Solna, Sweden（医学辐射物理学系，斯德哥尔摩大学）；Department of Oncology-Pathology, Karolinska Institutet, Solna, Sweden, Sweden（肿瘤病理学系，卡罗林斯卡研究所）；Division of Oncology and Children's Research Center, University Children's Hospital Zurich, Switzerland（肿瘤与儿童研究中心，苏黎世儿童医院）；Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University, Atlanta, USA（Wallace H. Coulter生物医学工程系，佐治亚理工学院和埃默里大学，美国）；Institute of Radiation Medicine (IRM), Helmholtz Zentrum München (HMGU), Germany（放射医学研究所（IRM），海德堡研究中心（HMGU））；German Consortium for Translational Cancer Research (DKTK), Partner Site Munich, Munich, Germany（德国转化癌症研究联盟（DKTK），慕尼黑合作伙伴站点）
