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Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention, Luping Zhou; Nicholas Heller; Yiyu Shi; Yiming Xia


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Автор: Luping Zhou; Nicholas Heller; Yiyu Shi; Yiming Xia
Название:  Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention
ISBN: 9783030336417
Издательство: Springer
Классификация:


ISBN-10: 3030336417
Обложка/Формат: Soft cover
Страницы: 154
Вес: 0.28 кг.
Дата издания: 2019
Серия: Image Processing, Computer Vision, Pattern Recognition, and Graphics
Язык: English
Издание: 1st ed. 2019
Иллюстрации: 48 illustrations, color; 14 illustrations, black and white; xx, 154 p. 62 illus., 48 illus. in color.
Размер: 234 x 156 x 10
Читательская аудитория: Professional & vocational
Основная тема: Computer Science
Подзаголовок: International Workshops, LABELS 2019, HAL-MICCAI 2019, and CuRIOUS 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Германии
Описание:

4th International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis (LABELS 2019).- Comparison of active learning strategies applied to lung nodule segmentation in CT scans.- Robust Registration of Statistical Shape Models for Unsupervised Pathology Annotation.- XiangyaDerm: A Clinical Image Dataset of Asian Race for Skin Disease Aided Diagnosis.- Data Augmentation based on Substituting Regional MRI Volume Scores.- Weakly supervised segmentation from extreme points.- Exploring the Relationship between Segmentation Uncertainty, Segmentation Performance and Inter-observer Variability with Probabilistic Networks.- DeepIGeoS-V2: Deep Interactive Segmentation of Multiple Organs from Head and Neck Images with Lightweight CNNs.- The Role of Publicly Available Data in MICCAI Papers from 2014 to 2018.- First International Workshop on Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention (HAL-MICCAI 2019).- Hardware Acceleration of Persistent Homology Computation.- Deep Compressed Pneumonia Detection for Low-Power Embedded Devices.- D3MC: A Reinforcement Learning based Data-driven Dyna Model Compression.- An Analytical Method of Automatic Alignment for Electron Tomography.- Fixed-Point U-Net Quantization for Medical Image Segmentation.- Second International Workshop on Correction of Brainshift with Intra-Operative Ultrasound (CuRIOUS 2019).- Registration of ultrasound volumes based on Euclidean distance transform.- Landmark-based evaluation of a block-matching registration framework on the RESECT pre- and intra-operative brain image data set.- Comparing deep learning strategies and attention mechanisms of discrete registration for multimodal image-guided interventions.



Дополнительное описание: 4th International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis (LABELS 2019).- Comparison of active learning strategies applied to lung nodule segmentation in CT scans.- Robust Registration of Statistical Shape Models f



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