Data Augmentation, Labelling, and Imperfections PDF Download

Author: Yuan Xue
Publisher: Springer Nature
ISBN: 3031581717
Category :
Languages : en
Pages : 178

View

Book Description

Author: Hien V. Nguyen
Publisher: Springer Nature
ISBN: 303117027X
Category : Computers
Languages : en
Pages : 134

View

Book Description
This book constitutes the refereed proceedings of the Second MICCAI Workshop on Data Augmentation, Labelling, and Imperfections, DALI 2022, held in conjunction with MICCAI 2022, in Singapore in September 2022. DALI 2022 accepted 12 papers from the 22 submissions that were reviewed. The papers focus on rigorous study of medical data related to machine learning systems.

Author: Sandy Engelhardt
Publisher: Springer Nature
ISBN: 3030882101
Category : Computers
Languages : en
Pages : 278

View

Book Description
This book constitutes the refereed proceedings of the First MICCAI Workshop on Deep Generative Models, DG4MICCAI 2021, and the First MICCAI Workshop on Data Augmentation, Labelling, and Imperfections, DALI 2021, held in conjunction with MICCAI 2021, in October 2021. The workshops were planned to take place in Strasbourg, France, but were held virtually due to the COVID-19 pandemic. DG4MICCAI 2021 accepted 12 papers from the 17 submissions received. The workshop focusses on recent algorithmic developments, new results, and promising future directions in Deep Generative Models. Deep generative models such as Generative Adversarial Network (GAN) and Variational Auto-Encoder (VAE) are currently receiving widespread attention from not only the computer vision and machine learning communities, but also in the MIC and CAI community. For DALI 2021, 15 papers from 32 submissions were accepted for publication. They focus on rigorous study of medical data related to machine learning systems.

Author: Yuan Xue
Publisher: Springer
ISBN: 9783031581700
Category : Computers
Languages : en
Pages : 0

View

Book Description
This LNCS conference volume constitutes the proceedings of the 3rd International Workshop on Data Augmentation, Labeling, and Imperfections (DALI 2023), held on October 12, 2023, in Vancouver, Canada, in conjunction with the 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023). The 16 full papers together in this volume were carefully reviewed and selected from 23 submissions. The conference fosters a collaborative environment for addressing the critical challenges associated with medical data, particularly focusing on data, labeling, and dealing with data imperfections in the context of medical image analysis.

Author: Zhiyun Xue
Publisher: Springer Nature
ISBN: 3031449177
Category : Computers
Languages : en
Pages : 274

View

Book Description
This book consists of full papers presented in the 2nd workshop of ”Medical Image Learning with Noisy and Limited Data (MILLanD)” held in conjunction with the 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023). The 24 full papers presented were carefully reviewed and selected from 38 submissions. The conference focused on challenges and limitations of current deep learning methods applied to limited and noisy medical data and present new methods for training models using such imperfect data.

Author: Yaqi Wang
Publisher: Springer Nature
ISBN: 3031723961
Category :
Languages : en
Pages : 202

View

Book Description

Author: Aleš Leonardis
Publisher: Springer Nature
ISBN: 3031726642
Category :
Languages : en
Pages : 577

View

Book Description

Author: Hayit Greenspan
Publisher: Springer Nature
ISBN: 3031439996
Category : Computers
Languages : en
Pages : 832

View

Book Description
The ten-volume set LNCS 14220, 14221, 14222, 14223, 14224, 14225, 14226, 14227, 14228, and 14229 constitutes the refereed proceedings of the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, which was held in Vancouver, Canada, in October 2023. The 730 revised full papers presented were carefully reviewed and selected from a total of 2250 submissions. The papers are organized in the following topical sections: Part I: Machine learning with limited supervision and machine learning – transfer learning; Part II: Machine learning – learning strategies; machine learning – explainability, bias, and uncertainty; Part III: Machine learning – explainability, bias and uncertainty; image segmentation; Part IV: Image segmentation; Part V: Computer-aided diagnosis; Part VI: Computer-aided diagnosis; computational pathology; Part VII: Clinical applications – abdomen; clinical applications – breast; clinical applications – cardiac; clinical applications – dermatology; clinical applications – fetal imaging; clinical applications – lung; clinical applications – musculoskeletal; clinical applications – oncology; clinical applications – ophthalmology; clinical applications – vascular; Part VIII: Clinical applications – neuroimaging; microscopy; Part IX: Image-guided intervention, surgical planning, and data science; Part X: Image reconstruction and image registration.

Author: Zhongying Deng
Publisher: Springer Nature
ISBN: 3031734718
Category :
Languages : en
Pages : 185

View

Book Description

Author: Ruidan Su
Publisher: Springer Nature
ISBN: 9811667756
Category : Technology & Engineering
Languages : en
Pages : 567

View

Book Description
This book covers virtually all aspects of image formation in medical imaging, including systems based on ionizing radiation (x-rays, gamma rays) and non-ionizing techniques (ultrasound, optical, thermal, magnetic resonance, and magnetic particle imaging) alike. In addition, it discusses the development and application of computer-aided detection and diagnosis (CAD) systems in medical imaging. Given its coverage, the book provides both a forum and valuable resource for researchers involved in image formation, experimental methods, image performance, segmentation, pattern recognition, feature extraction, classifier design, machine learning / deep learning, radiomics, CAD workstation design, human–computer interaction, databases, and performance evaluation.